Linux-based Edge Gateways that connects hundreds or maybe thousands of IoT devices, are exposed to various threats and cyber-attacks from the internet. These attacks form a considerable risk targeting the privacy and confidentiality of IoT devices throughout their gateways. Many researches and studies have been conducted to alleviate such a problem. One of the solutions can be achieved by building a root of trust based on a hardware module such as Trusted Platform Module (TPM) or software like Trusted Execution Environment (TEE). In this work, we provide a solution to the problem by enabling Hardware Root of Trust (HRoT) using TPM on a product from HMS Industrial Network AB known as GWen board, a Linux-based embedded system, used as gateway to connect IoT devices. We describe a method that uses the processor of the GWen (i.e. Zynq-7020 FPGA SoC) to enable secure boot. Besides, we provide a method to enable the TPM chip mounted on the GWen (i.e. SLB 9670 TPM 2.0) using TPM Software Stack TSS 2.0. We demonstrated, in detail, various use-cases using the TPM on GWen including cryptographic keys generation, secure key storage and key usage for different cryptographic operations. Furthermore, we conducted an analysis to the adopted solution by inspecting the latency of TPM commands on the GWen gateway. According to the high restrictions of TPM 2.0 specifications and based on our results, adding the TPM 2.0 to the IoT gateway GWen will enhance the security of its Linux distribution and will makes it possible to securely identify and authenticate the gateway on the network based on its secret keys that are stored securely inside its TPM.

This work presents an energy system design for wireless sensor networks (WSNs) after applying our design the WSN should theoretically have an infinite lifetime. Energy harvesting sources can provide suitable energy for WSN nodes and reduce their dependence on battery. In this project, an efficient energy harvesting and storage system is proposed. By using (two supercapacitors and four DC/DC converters with step up /step down capabilities) all of them controlled by Microcontroller via switches to consider the best way to save energy to keep the WSN alive as long as possible. The usage of supercapacitors as an energy buffer to supply the sensor components (microcontroller and radio) with energy it needs to work. We could control the energy flow according to a specific voltage levels in supercapacitors to guaranty the full functionality for WSN with minimizing the loss of energy, and that’s leads to long time life for the wireless sensor node WSN. Another important thing we find in our experiment that is the inner leakage of the supercapacitor and how it has a critical effect on how long it can serve our system with energy. This paper contains on two theoretical sections (Part one and part two) which are based on literature reviews, and one experimental section (Part three) based on experimental building the prototype, coding and testing.

All forecasts of Internet trac point at a substantial growth over the next few years. From a network operator perspective, efficient in-network caching of data is and will be a key component in trying to cope with and profit from this increasing demand. One problem, however, is to evaluate the performance of different caching policies as the number of available data items as well as the distribution networks grows very large.

In this work, we develop an analytical model of an aggregation access network receiving a continuous flow of requests from external clients. We provide exact analytical solutions for cache hit rates, data availability and more. This enables us to provide guidelines and rules of thumb for operators and Information-Centric Network designers.

Finally, we apply our analytical results to a real VoD trace from a network operator and show that substantial bandwidth savings can be expected when using in-network caching in a realistic setting.

Video content, of which YouTube is a major part, constitutes a large share of residential Internet traffic. In this paper, we analyse the user demand patterns for YouTube in two metropolitan access networks with more than 1 million requestsover three consecutive weeks in the first network and more than 600,000 requests over four consecutive weeks in the second network.

In particular we examine the existence of “local interest communities”, i.e. the extent to which users living closer to each other tend to request the same content to a higher degree, and it is found that this applies to (i) the two networks themselves; (ii) regions within these networks (iii) households with regions and (iv) terminals within households. We also find that different types of access devices (PCs and handhelds) tend to form similar interest communities.

It is also found that repeats are (i) “self-generating” in the sense that the more times a clip has been played, the higher the probability of playing it again, (ii) “long-lasting” in the sense that repeats can occur even after several days and (iii) “semi regular”in the sense that replays have a noticeable tendency tooccur with relatively constant intervals.

The implications of these findings are that the benefits from large groups of users in terms of caching gain may be exaggerated, since users are different depending on where they live and what equipment they use, and that high gains can be achieved in relatively small groups or even for individual users thanks totheir relatively predictable behaviour.

The coverage areas of cellular networks are logically subdivided into service areas. Each service area has a local anchor node which “hides” the mobility inside the area and the entire network has a global anchor node which “hides” the mobility between areas.

The concept of unique local anchor nodes per service area was invented to simplify routing but has been found to complicate expansion. The rapidly growing demand for cellular access has therefore prompted for alternative solutions with pools of local anchor nodes per service area. Such pools are now deployed by several operators all over the world.

Users in pooled service areas are mapped to specific pool members according to a load distribution policy, but the mapping can change as a result of node failures or operator interventions. Such changes take a certain time to implement and cause additional load on the anchor nodes. We study these processes in detail and derive closed form expressions which allow operators to control the trade-off between rapid changes and acceptable loads.

Finally we show that the key assumptions of our model are in agreement with measured data and demonstrate how the model can be applied to investigate the effects of different network settings (timers) under different user behaviour (traffic and mobility).

Contrary to current solutions to this problem, which typically are slow and/or inaccurate, our results enable fast and accurate analysis of different scenarios thereby enabling operators to maximise utilisation of the existing investments and at the same time avoid potentially dangerous situations of overload.

We consider TCP performance for cloud servicesin 5G cellular networks and show that edge clouds offer the highest throughput, but that further improvements still arepossible. To this end we devise a concept where edge clouds connected directly to the radio access network can increase their transmission rates by relying on the built in re-transmissions (through quality of service features) and on the built in userfairness (through per-user buffers and scheduler policies). We use numerical examples from measurements in real networks to demonstrate that the concept is efficient and significantly improves the effective throughput beyond what placement alone can do, and we also outline possible further improvements.

We consider bottlenecks of TCP throughput in scenarios with edge clouds and 5G cellular networks. By numerical examples from measurements in real networks, we show that edge clouds indeed improve throughput but that several, nonnegligible bottlenecks remain. We therefore devise a concept where edge clouds connected directly to the radio access networkcan increase their transmission rates by relying on built in retransmissions (through quality of service features) and on the built in user fairness (through per-user buffers and scheduler policies). We then return to the numerical examples and show that our solution provides substantial gains and we concludeby identifying and discussing the remaining bottlenecks and the potential of an improved protocol.

Quantifying quality of experience for network applications is challenging as it is a subjective metric with multiple dimensions such as user expectation, satisfaction, and overall experience. Today, despite various techniques to support differentiated Quality of Service (QoS), the operators still lack of automated methods to translate QoS to QoE, especially for general web applications.

In this work, we take the approach of identifying unsatisfactory performance by searching for user initiated early terminations of web transactions from passive monitoring. However, user early abortions can be caused by other factors such as loss of interests. Therefore, naively using them to represent user dissatisfaction will result in large false positives. In this paper, we propose a systematic method for inferring user dissatisfaction from the set of early abortion behaviors observed from identifying the traffic traces. We conduct a comprehensive analysis on the user acceptance of throughput and response time, and compare them with the traditional MOS metric. Then we present the characteristics of early cancelation from dimensions like the types of URLs and objects. We evaluate our approach on four data sets collected in both wireline network and a wireless cellular network.

In an increasingly competitive environment it is more important than ever for operators to keep their end users satisfied. User satisfaction is often characterised in terms of Quality of Experience (QoE), a subjective metric with multiple dimensions such as expectations, content, terminal, environment, cost and performance. QoE is typically quantified as MOS, mean opinion score, which is obtained by averaging the ranks of a number of voluntary users for controlled combinations content/terminals/performance etc. While this approach has many advantages, there are also a number of difficulties such as representativeness (the number of users as well as the number of objects and devices all have to be kept small); validity (the results may be biased by the situation, the setting, the renumeration and so on); and applicability (it is not clear how different numbers map to notions such as “acceptable” or “unacceptable” and operators alone cannot do very much about factors such as content).

We thus investigate the possibilities of detecting user opinions in the above, simplified, terms and from the network itself; with actual expectations, content, terminals, environments, costs and performance for virtually all users all the time. To this end we revisit the earlier suggestion that user opinions be reflected in their behaviour such that poor performance may result in interrupted requests. These works have, however, considered single flows hence we extend that idea to web pages which are groups of flows. In this paper we present our methods to group flows, interpret users, and characterise performance and we make a first assessment of the correlations between web page interruptions and network performance characteristics.

Mobile internet has been widely adopted and it is expected to rise to almost 4 billion users by 2020. Despite the research effort dedicated to the enhancement of its performance, there still exists a gap in the understanding of how TCP and its many variants work over LTE. To this end, this paper evaluates the extent to which five common TCP variants, CUBIC, NewReno,Westwood+, Illinois, and CAIA Delay Gradient (CDG), are able to utilise available radio resources under hard conditions, such as during start-up and in mobile scenarios at different speeds. The paper suggests that CUBIC, due to its Hybrid Slow-Start mechanism, enters congestion avoidance prematurely, and thus experiences a prolonged start-up phase. As a result, it is unable to efficiently utilise radio resources during shorter transmissionsessions. Besides, CUBIC, Illinois and NewReno, i.e., the loss-based TCP implementations, offer better throughput, and are able to better utilise available resources during mobility than Westwood+ and CDG - the delay-based variants do.

Internet traffic from a fibre based residential access network is investigated concerning traffic volumes and link load. Also the cost of the services is analyzed. We show that 1 Mbps accesses subscribers maintain high loads, and that the price they pay per GB used is five times higher than the one paid by 100 Mbps access subscribers.

Since the purchase of Siri by Apple, and its release with the iPhone 4S in 2011, virtual assistants (VAs) have grown in number and popularity. The sophisticated natural language processing and speech recognition employed by VAs enables users to interact with them conversationally, almost as they would with another human. To service user voice requests, VAs transmit large amounts of data to their vendors; these data are processed and stored in the Cloud. The potential data security and privacy issues involved in this process provided the motivation to examine the current state of the art in VA research. In this study, we identify peer-reviewed literature that focuses on security and privacy concerns surrounding these assistants, including current trends in addressing how voice assistants are vulnerable to malicious attacks and worries that the VA is recording without the user’s knowledge or consent. The findings show that not only are these worries manifold, but there is a gap in the current state of the art, and no current literature reviews on the topic exist. This review sheds light on future research directions, such as providing solutions to perform voice authentication without an external device, and the compliance of VAs with privacy regulations. 

TV-on-Demand services have become one of the most popular Internet applications that continuously attracts high user interest. With rapidly increasing user demands, the existing network conditions may not be able to ensure a low start-up delay of video playback. Prefetching has been broadly investigated to cope with the start-up latency problem, which is also known as user perceived latency. In this paper, two datasets from different IPTV providers are used to analyse the TV program request patterns. According to the results, we propose a prefetching scheme at the user end to preload videos before user requests. For both datasets, our prefetching scheme significantly improves the cache hit ratio compared to passive caching and we note that there is a potential to further improve prefetching performance by customizing prefetching schemes for different video categories. We further present a cost model to determine the optimal number of videos to prefetch. We also discuss if there is enough time for prefetching. Finally, more factors, which may have an impact onoptimizing prefetching performance, are further discussed, such as the jump patterns over different time in a day and the the distribution of each video’s viewing length.

TV-on-Demand service has become one of the most popular Internet applications that continuously attracts higher user interests. With rapidly increasing user demand, the existing network conditions may not be able to ensure low start-up delay of video playback. Prefetching has been broadly investigated to cope with the start-up latency problem which is also known as user perceived latency. In this paper, we analyse request patterns for TV programs from a popular Swedish TV service provider over 11 weeks. According to the analysis, we propose a prefetching scheme at the user end to preload videos before user requests. Our prefetching scheme significantly improves the cache hit ratio compared to terminal caching and we note that there is a potential to further improve prefetching performance by customizing prefetching schemes for different video categories. We further present a cost model to determine the optimal number of videos to prefetch. Finally, we discuss available time for prefetching and suggest that when to make prefetching decisions depends on the user demand patterns of different video categories.

 I den här studien har vi undersökt vilka faktorer för interaktion som påverkar användarupplevelser vid digitalisering med AI (Artificiell Intelligens). Det vår analys och slutsats pekar på är faktorer som: otydlighet, inkonsekvens i interaktioner, brist på feedback och information men även personliga samtal och väntetider. Våra empiriska undersökningar visar på att dessa faktorer påverkar upplevelserna på olika sätt, både negativt och positivt. Genom att beakta dessa faktorer samt även möjligheterna som digitalisering med AI ger, kan detta bidra till att skapa önskvärda användarupplevelser. Våra studier har resulterat i ett designförslag där vi föreslår att AI används för rutinuppgifter, bedömningar och för att stödja dokumentation.

Studien är relevant i och med att vi har identifierat att det finns luckor i tidigare forskning om just kopplingen mellan användarupplevelse, digitalisering och AI.

Vi har använt kvalitativa metoder för de empiriska undersökningarna: observation och intervjuer. Vi har även genomfört en workshop för att undersöka det designförslag vi kommit fram till.

Vi vill peka på att resultatet av våra undersökningar är relevant för de digitaliseringsprojekt som pågår idag, men vi ser även att det krävs vidare studier i form av att en utveckling av den föreslagna lösningen genomförs och testas, samt att man undersöker användarupplevelse vid digitalisering med AI vidare med flera fall.

This degree project deals with electronic health record (EHR). The report is divided into two main sections; literature study on electronic health record and an EHR system implementation. In the literature study section, EHR background, development history and service condition are introduced. The paper focuses on the sharing of medical information in different users, data safety and privacy. The adjunctions of computer science, technologies are used to solve the medical informatics’ problems. In the implementation section, based on the study of the current EHR systems, the design and implement of a shared EHR system are presented, which can be accessed by different doctors and patients. Access control function and cryptography protections are included in this system. The system test and evaluation are also given.

This degree project deals with a website that can help people to save, share and utilize their dreams and wishes. Communication is the most important part of our social life and iDream is

programmed to take dreams and wishes to a social level by creating better understanding

between people through dreams and wishes.

It allows people to create dream/wish blogs, read others blogs through a gallery, subscribing to other people’s blogs and getting automatic feed from subscribed blogs. Popular blogs become a community which can maximize the effect of the dream or wish and finally an option to add family members and see their activities.

Joomla CMS is the core of the website. The project also includes research on efficient Joomla component creation and 3D website design according to Human-computer interaction principles.

Data volumes in communication networks increase rapidly. Further, usage of social network applications is very wide spread among users, and among these applications, Facebook is the most popular. In this paper, we analyse user demands patterns and content popularity of Facebook generated traffic. The data comes from residential users in two metropolitan access networks in Sweden, and we analyse more than 17 million images downloaded by almost 16,000 Facebook users. We show that the distributions of image popularity and user activity may be described by Zipf distributions which is favourable for many types of caching. We also show that Facebook activity is more evenly spread over the day, compared to more defined peak hours of general Internet usage. Looking at content life time, we show that profile pictures have a relatively constant popularity while for other images there is an initial, short peak of demand, followed by a longer period of significantly lower and quite stable demand. These findings are useful for designing network andQoE optimisation solutions, such as predictive pre-fetching, proxy caching and delay tolerant networking.

Internet of Things facilitates interaction betweenhuman users and physical environment through the use ofelectronic sensors, wireless communication and cloudtechnology. In this paper, we demonstrate a scalableimplementation of Internet of Things in a lab environment. Aversatile set of sensors including cameras, power outlets andordinary temperature sensors are embedded in the physicalenvironment and connected to the cloud via local gateways. Datais processed locally and accessible via the cloud. A web servicehosted in the cloud enables remote two-way interaction betweenthe human users and the monitored physical environments.

Today, cellular networks rely on fixed collections of cells (tracking areas) for user equipment localisation. Locating users within these areas involves broadcast search (paging), which consumes radio bandwidth but reduces the user equipment signalling required for mobility management. Tracking areas are today manually configured, hard to adapt to local mobility and influence the load on several key resources in the network. We propose a decentralised and self-adaptive approach to mobility management based on a probabilistic model of local mobility. By estimating the parameters of this model from observations of user mobility collected online, we obtain a dynamic model from which we construct local neighbourhoods of cells where we are most likely to locate user equipment. We propose to replace the static tracking areas of current systems with neighbourhoods local to each cell. The model is also used to derive a multi-phase paging scheme, where the division of neighbourhood cells into consecutive phases balances response times and paging cost. The complete mechanism requires no manual tracking area configuration and performs localisation efficiently in terms of signalling and response times. Detailed simulations show that significant potential gains in localisation efficiency are possible while eliminating manual configuration of mobility management parameters. Variants of the proposal can be implemented within current (LTE) standards.

Today, cellular networks rely on fixed collections of cells (tracking areas) for handset localisation. This management parameter is manually configured and maintained and is not regularly adapted to changes in use patterns. We present a decentralised approach to localisation, based on a self-adaptive probabilistic mobility model. Estimates of model parameters are built from observations of mobility patterns collected online using a distributed algorithm. Based on these estimates, dynamic local neighbourhoods of cells are formed and maintained by the mobility management entities of the network. These neighbourhoods replace the static tracking areas used in current implementations by using the tracking area list facility of LTE. The model is also used to derive a multi phase paging scheme, where the division of cells into consecutive phases is optimal with respect to a set balance between response times and paging cost. The approach requires no manual tracking area configuration, and performs localisation efficiently in terms of number of location updates, page

This degree project deals with license management for EBITool. It´s about providing protection and monitoring for a Java Application via a license server, and the construction of it. An analysis that discusses the approach and other possible courses of action is also included. Additionally, it covers a discussion of a prototype implementation of the model solution from the analysis.

The prototype is a Java EE application that deploys to JBoss AS7. It´s developed using the JBoss Developer Studio 5.0.0, an Eclipse IDE with JBoss Tools preinstalled. It exposes web services to Java Applications through SOAP via JAX-WS. Using Hibernate, the web service Enterprise Java Beans get access to a PostgreSQL 9.1 database via entity classes mapped to the database through the Java Persistence API.

These days, healthcare applications on the Internet of Medical Things (IoMT) network have been growing to deal with different diseases via different sensors. These healthcare sensors are connecting to the various healthcare fog servers. The hospitals are geographically distributed and offer different services to the patients from any ubiquitous network. However, due to the full offloading of data to the insecure servers, two main challenges exist in the IoMT network. (i) Data security of workflows healthcare applications between different fog healthcare nodes. (ii) The cost-efficient and QoS efficient scheduling of healthcare applications in the IoMT system. This paper devises the Cost-Efficient Service Selection and Execution and Blockchain-Enabled Serverless Network for Internet of Medical Things system. The goal is to choose cost-efficient services and schedule all tasks based on their QoS and minimum execution cost. Simulation results show that the proposed outperform all existing schemes regarding data security, validation by 10%, and cost of application execution by 33% in IoMT.

These days, with the emerging developments in wireless communication technologies, such as 6G and 5G and the Internet of Things (IoT) sensors, the usage of E-Transport applications has been increasing progressively. These applications are E-Bus, E-Taxi, self-autonomous car, E-Train and E-Ambulance, and latency-sensitive workloads executed in the distributed cloud network. Nonetheless, many delays present in cloudlet-based cloud networks, such as communication delay, round-trip delay and migration during the workload in the cloudlet-based cloud network. However, the distributed execution of workloads at different computing nodes during the assignment is a challenging task. This paper proposes a novel Multi-layer Latency (e.g., communication delay, round-trip delay and migration delay) Aware Workload Assignment Strategy (MLAWAS) to allocate the workload of E-Transport applications into optimal computing nodes. MLAWAS consists of different components, such as the Q-Learning aware assignment and the Iterative method, which distribute workload in a dynamic environment where runtime changes of overloading and overheating remain controlled. The migration of workload and VM migration are also part of MLAWAS. The goal is to minimize the average response time of applications. Simulation results demonstrate that MLAWAS earns the minimum average response time as compared with the two other existing strategies.

Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system.

In this paper we study traffic patterns in a large municipal WiFi network and in particular those of the most bandwidth hungry application, viz. YouTube, for which we provide a detailed analysis of demand in different geographical areas and over time. We consider the possibilities to reduce network traffic and increase Quality of Experience (QoE) by serving repeated requests for YouTube videos from caches placed either at the network head end, at the wireless access points, or in the user devices. Our data confirms that a significant part of the YouTube traffic can be served by such devices and that there exists a potential to optimize caching performance by exploiting the content demand locality. We also discover a previously unknown pattern of periodicity in content demand and present a simple example of how to exploit this in cache design.

In this work, we study YouTube traffic characteristics in a medium-sized Swedish residential municipal network that has ~ 2600 mainly FTTH broadband-connected households. YouTube traffic analyses were carried out in the perspective of video clip category and duration, in order to understand their impact on the potential local network caching gains. To the best of our knowledge, this is the first time systematic analysis of YouTube traffic content in the perspective of video clip category and duration in a residential broadband network. Our results show that the requested YouTube videoclips from the end users in the studied network were imbalanced in regarding the video categories and durations. The dominating video category was Music, both in terms of the total traffic share as well as the contribution to the overall potential local network caching gain. In addition, most of the requested video clips were between 2-5 min in duration, despite video clips with durations over 15 min were also popular among certain video categories, e.g. film videos.

In this paper we describe a systematic study on long-term evolution of residential broadband Internet traffic covering 5 calendar years from June 2007 to May 2011. The traffic evolution is characterized both in the term of the total traffic volume, as well as the traffic volumes and shares for different application categories (file sharing, video streaming etc.), with the focus on comparing the traffic on the per IP user basis and among different broadband subscription groups. The results show that the average daily total traffic generated by each private end user increased only by about 33 % during the past 5 years. Further, the results show that the P2P filesharing has been dominating the network total traffic, but the daily file-sharing traffic volume per end user largely remains the same. Also, the daily streaming-media traffic volume per end user has increased dramatically by over 500% during the studied period of time. In the meantime, the daily web-browsing traffic volume per end user has increased by about 300%. Finally, a further investigation among 4 different FTTH broadband subscription groups with 1, 10 , 30, and 100 Mbit/s symmetric access speeds shows that the lower the access speed, the more diversified the end user traffic tend to be.

In this work, the performance of 5 representative caching replacement policies was investigated and compared for caching Internet video-on-demand (VoD) in local access networks. Two measured traces of end-user requests were used in the analyses for two typical VoD services: TV-on-demand and user generated content represented by YouTube. The studied policies range from simple least recently used (LRU) and least frequently used (LFU) algorithms to more advanced ones denoted as LFU-dynamic lifespan (LFU-DL), Adaptive replacement cache (ARC) and Greedy-dual size frequency (GDSF). Our results show that the ARC policy always outperforms the other policies due to its adaptive nature and its ability to track changes in the traffic patterns. On the other hand, the simple LRU policy can also achieve a caching performance which is comparable to that of the more advanced ARC policy especially for the TV-on-demand service when the potential caching gain is high. On the contrary, the simple LFU policy always shows the poorest performance.However, by applying a proper lifespan supplement under the LFU-DL policy, the caching performance can be effectively enhanced to the level achievable using ARC and LRU policies. Moreover, the GDSF policy does not outperform simple LRU or LFU-DL, especially for YouTube video clips when the potential caching gain is relatively low. The advantage of GDSF manifested in our analysis is, however, its outstanding cache space usage efficiency among the five studied caching algorithms.

Distribution of media data over the Internet is increasing in popularity and volume. This poses challenges not only for network operators but also for service providers when it comes to serving the demand in a cost-efficient way. In this paper, we approach this problem by investigating the potential of co-operative approaches where locality in space (users in the same network) and locality in time (concurrent downloads) are exploited such that as many requests as possible may behandled inside the access and metro networks. This approach may contribute not only to reducing transport costs (less traffic in core networks and at peering points) by but also improve the end user experience (by reduced round trip times and exclusion of some possible bottlenecks). To this end we develop a method to measure the possible gains from, firstly, optimal handling of concurrent downloads and, secondly, optimal utilization localavailability. We apply the method to BitTorrent data from two metropolitan access networks and find that the bandwidth savings amount to between 10% and 20% when optimizing concurrent downloads and between 56% and 66% when exploiting local availability with a simulated network cache.

This degree project deals with creating an Android application for managing representation orders placed in stores as well as evaluating Androids usage as a platform for that line of work. The evaluation will be based on tests of the application on an Android phone together with a survey consisting of written questions and a practical test of the application.

Vad är BYOD (Bring Your Own Device)? BYOD är en relativt ny trend som går ut på att anställda på ett företag får möjlighet att ta med sina egna elektroniska produkter såsom smarta telefoner, surfplattor och bärbara datorer. Det dyker upp rubriker om fenomenet BYOD (Bring Your Own Device) i diverse tekniska nättidningar och under utbildningens gång har det funnits lärare som berört ämnet lite löst. Detta väckte en nyfikenhet för att gräva djupare i ämnet, eftersom det verkade vara en trend på uppgång. Detta är en så pass ny företeelse att många företag inte vet hur de ska hantera detta i sitt nätverk. Företagen har också fått omvärdera sina säkerhetspolicys.

This paper presents our work regarding the comparison of the behaviour of some of the major TCP variants in a LTE network. Using the LENA LTE simulator and the DCE framework, the behaviour of the Linux implementations of seven TCP variants are compared. The evolution of the throughput, congestion window and queuing delay are studied for four scenarios with different network loads and flow types. Our measurements show that, in the situations we consider, most variants are able to quickly reach full link utilisation. However, to reach the same throughput, they create different amounts of queuing delay. On the one hand, loss based algorithms tend to totally fill the queue, creating huge queuing delays and inducing packet losses. On the other hand, delay based variants manage to limit the queue size and decrease the amount of packet dropped by the eNodeB but struggle to reach the maximum throughput in some circumstances.

This project includes an implementation of an intelligent voice recognition assistant for Android where functionality on current existing applications on other platforms is compared. Until this day, there has not been any good alternative for Android, so this project aims to implement a voice assistant for the Android platform while describing the difficulties and challenges that lies in this task.

There is currently an ongoing digital transformation for sewage and wastewater management. By automating data collection and enabling remote monitoring, we will not only be able to save abundant human resources but also enabling predictive maintenance which is based on big data analytics. This paper presents a smart sewage water management system which is currently under development in southern Sweden. Real-time data can be collected from over 500 sensors which have already been partially deployed. Preliminary data analysis shows that we can build statistical data models for ground water, rainfall, and sewage water flows, and use those models for data forecast and anomaly detection.

Människor använder sig allt mer av digitala hälsoplattformar, vilket gör att det genereras mängder av hälsodata från användarnas digitala aktiviteter. Syftet med detta examensarbetet är att med hjälp av en konceptdriven designforskning framställa ett designkoncept för att hantera denna stora mängd hälsodata. Målet med konceptet är att det ska skapa en möjlighet för individer att själva hantera och få tillgång till sin hälsodata som genereras, för att i sin tur även kunna utnyttja det till något meningsfullt. 

Med hjälp av en metodologisk guide har konceptet utvecklats, för att ta fram teoretiskt förankrade egenskaper och sammanställa dem till ett koncept i form av en modell. För att få in extern kritik av konceptet involverades tio användare, vilket i sin tur ledde till revidering och kontextualisering av HealthLab. I resultatet presenteras slutgiltligt koncept av Healthlab. Konceptet ska fungera som en multiplattform vars syfte är att samla in externa hälsodata, för att användarna ska få in flera aspekter i deras träning, som ska i sin tur hjälpa till att bidra till en bättre träningsupplevelse. Det slutgiltiga resultatet av HealthLab är tänkt att vara en framtidsvision för att vägleda och väcka nya tankesätt hos forskare och designers. 

Because of rapidly growing subscriber populations, advances in cellular communication technology, increasingly capable user terminals, and the expanding range of mobile applications, cellular networks have experienced a significant increase in data traffic, the dominant part of which is carried by the http protocol. Understanding the characteristics of this traffic is important for network design, traffic modeling, resource planning and network control. In this study we present a comprehensive characterization study of mobile http-based traffic using packet level traces collected in a large cellular network. We analyze the traffic using metrics at packet level, flow level and session level. For each metric, we conduct a comparison between traffic from different applications, as well as comparison to traffic in a wired network. Finally, we discuss the implications of our findings for better resource utilization in cellular infrastructures.

Data traffic in cellular networks increased tremendously over the past few years and this growth is predicted to continue over the next few years. Due to differences in access technology and user behavior, the characteristics of cellular traffic can differ from existing results for wireline traffic. In this study we focus on understanding the flow rates and on the relationship between the rates and other flow properties by analyzing packet level traces collected in a large cellular network. To understand the limiting factors of the flow rates, we further analyze the underlying causes behind the observed rates, e.g.,network congestion, access link or end host configuration. Our study extends other related work by conducting the analysis from a unique dimension, the comparison with traffic in wired networks, to reveal the unique properties of cellular traffic. We find that they differ in variability and in the dominant rate limiting factors.

An image processing method for automatic quality assurance of Ericsson products is developed. The method consists of taking an image of the product, extract the product labels from the image, OCR the product numbers and make a database lookup to match the mounted product with the customer specification. The engineering innovation of the method developed in this report is that the OCR is performed using machine learning techniques. It is shown that machine learning can produce results that are on par or better than baseline OCR methods. The advantage with a machine learning based approach is that the associated neural network can be trained for the specific input images from the Ericsson factory. Imperfections in the image quality and varying type fonts etc. can be handled by properly training the net, a task that would have been very difficult with legacy OCR algorithms where poor OCR results typically need to be mitigated by improving the input image quality rather than changing the algorithm.

With the amount of programming languages currently available there is a high risk of confusion anddoubtfulness in aspiring programmers of which to choose. It may be motivating for a beginner tochoose “the perfect language” when starting, to avoid learning multiple languages. This thesiscompares three popular languages on three separate aspects, their syntax, usefulness in differentareas, and performance in terms of speed. Syntax wise the results varied with some aspects beingvery similar across all three languages to completely different in others. In terms of usefulness inspecific areas the languages flexibility allowed them to develop applications in most fields, while beingdominant in different areas. The speed comparison resulted in python being the slowest across alltests, with Java and Javascript (running inside Nodejs) competing for first place.