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Software-Defined Networking (SDN) architecture was developed to address the shortcomings of traditional network architectures. It allows system administrators to easily manage and configure the network by separating and abstracting the control plane from the data plane. All the knowledge and intelligence of SDN is concentrated in a software entity called the SDN controller, making the network programmable. However, a large-scale SDN architecture, particularly in the IoT domain, requires the implementation of a physically distributed control mechanism. Such a mechanism, based on the East/West interface raises many challenges in terms of scalability, reliability, security, consistency, and traceability. The development of the Blockchain allows addressing some of these challenges. In this paper, we present a design using Blockchain technology to improve SDNs in terms of trackability and discuss the adaptations required for large-scale deployment. Experimental results clearly show that the use of a proof-of-authority consensus algorithm in combination with a Merkle tree approach reduces the impact in terms of latency as well as in terms of Gas consumption.

Towards the next generation networks, low earth orbit (LEO) satellites have been considered as a promising component for beyond 5G networks. In this paper, we study downlink LEO-5G communication systems in a practical scenario, where the integrated LEO-terrestrial system is over-loaded by serving a number of terminals with high-volume traffic requests. Our goal is to optimize resource scheduling such that the amount of undelivered data and the number of unserved terminals can be minimized. Due to the inherent hardness of the formulated quadratic integer programming problem, the optimal algorithm requires unaffordable complexity. To solve the problem, we propose a near-optimal algorithm based on alternating direction method of multipliers (ADMM-HEU), which saves computational time by taking advantage of the distributed ADMM structure, and a low-complexity heuristic algorithm (LC-HEU), which is based on estimation and greedy methods. The results demonstrate the near-optimality of ADMM-HEU and the computational efficiency of LC-HEU compared to the benchmarks.

Wireless devices have been used to investigate the environment and to understand our physical world. In this work, we undertake the challenging problem of identifying location of obstacles and objects by WiFi signals. Gathering wireless sensory data to form an image is difficult since wireless signals are susceptible to multipath. Moreover, reconstructing an image of unknown objects based on the measurements of sparse signals is an ill-posed problem. To tackle these problems, we first present a linear model using received signal strength indicator (RSSI) measurements. We define the sparse beamforming problem as an l(0)-norm optimization problem, then use the iterative reweighted l(1) heuristic algorithm to obtain an optimal solution as a multipath. Finally, the multipath fading is removed by using Machine Learning. More specifically, we use Support Vector Regression (SVR) to identify a clear image of the unknown object. Our results show that the proposed method can reconstruct signals as a 3D image with a satisfactory visual appearance, i.e. the generated data mesh is well defined and smooth compared to previous work., Funding Agencies|strategic innovation programme Smart Built Environment - Vinnova; FormasSwedish Research Council Formas; Energimyndigheten

Use of wireless signal for identification of unknown object, or technology to see-through a wall to form an image, is gaining growing interest from various fields including law enforcement and military sectors, disaster management, or even in civilian sectors such as construction sites. The great challenge in the implementation of such technology is the stochastic disturbances on wireless signal which will result in a signal with missing samples. Compressive Sensing (CS) is a powerful tool for estimating the missing samples since it can find accurate solution to largely underdetermined linear wireless signals. However, sparse models like CS can also suffer from information loss dues to stochastic lossy nature of wireless, making CS not to have accurate information for reconstruction of a signal. In this paper, we developed a theoretical and experimental framework for the mapping of obstacles by reconstructing the wireless signal based on a sparse signal. We apply tensor format to perform the computations along each mode by relaxing the tensor constraints to obtain accurate results. The proposed framework demonstrates how to take 2D signals, formulate estimate signals and produce a 3D image location in a completely unknown area inside of the obstacle (wall)., Funding Agencies|strategic innovation programme Smart Built Environment; VinnovaVinnova; FormasSwedish Research Council Formas; Energimyndigheten

It is a critical requirement of the future 5G communication networks to provide high speed and significantly reduce the network energy consumption. Energy efficient networks along with an energy saving strategy in mobile devices play a vital role in the mobile revolution. The new strategies should not only focus on wireless base stations, which consumes most of the power, but also considers the other power consumption elements for future mobile communication networks, including User Equipment (UE). In this paper, we have proposed a method that calculates the power consumption of a 5G network by considering its main elements based on current vision of 5G network infrastructure. Our proposed model uses the component based methodology that simplifies the process by taking into account the different high power consuming elements. The proposed method is evaluated by considering the three UEs DRX models and Virtual Base Station (VBS) with respect to different DRX timer in terms of Power Saving (PS) and delay as performance parameters.

Wireless radio-frequency (RF) technologies has had universal wide-scale deployment. Despite this, the practical limitations of the RF spectrum being unable to meet the challenges (e.g. lack of security, high interference, limited bandwidth, scalability) of RF based communication networks have become increasingly apparent over the past decade. With the evergrowing of data heavy wireless communications, especially on the last mile (e.g. wireless mesh network) and the backbone, methods are required to help addresses the problem RF have been facing for the next generation network. Faced with such daunting obstacles in RF-only networks, the use of Free Space Optical (FSO) for wireless communications was proposed. FSO is a promising solution to security, limited spectrum bandwidth, the scalability problem of wireless mesh networks, but also the advantage of large transmission distance, free license, interference immunity, and high-bandwidth. Despite the major advantages of FSO technology, its widespread use has been hampered by atmospheric turbulence-induced fading. However, FSO is still consider to be a practical solution to RF challenges. To maximize the potential of FSO networks, we study the problem of maximum path resource flow for a route and minimum linear delay while the FSO topology under atmospheric turbulence. Such methods can be easy adopted to SDN to manage the data flow at the linkor network-layer.

The 4G standard Long Term Evolution (LTE) has been developed for high-bandwidth mobile access for today's data-heavy applications, consequently, a better experience for the end user. Since cellular communication is ready available, LTE communication has been designed to work at high speeds for vehicular communication. The challenge is that the protocols in LTE/LTE-Advanced should not only provide good packet delivery but also adapt to changes in the network topology due to vehicle volume and vehicular mobility. It is a critical requirement to ensure a seamless quality of experience ranging from safety to relieving congestion as deployment of LTE/LTE-Advanced become common. This requires learning how to improve the LTE/LTE-Advanced model to better appeal to a wider base and move toward additional solutions. In this paper we present a feasibility analysis for performing vehicular communication via a queueing theory approach based on a multi-server queue using real LTE traffic. A M/M/m model is employed to evaluate the probability that a vehicle finds all channels busy, as well as to derive the expected waiting times and the expected number of channel switches. Also, when a base station (eNB) becomes overloaded with a single-hop, a multi-hop rerouting optimization approach is presented.

Single carrier frequency division multiple access (SC-FDMA) has been adopted as the standard multiple access scheme for 3GPP LTE uplink. In comparison to orthogonal frequency division multiple access (OFDMA), the subcarriers assigned to each user are required to be consecutive in SC-FDMA localized scheme, which imposes more difficulties on resource allocation problem. Subject to this constraint, various optimization objectives, such as utility maximization and power minimization, have been studied for SC-FDMA resource allocation. In this paper, we focus on developing a general algorithm framework with near-optimal performance and polynomial-time complexity to maximize the total utility for SC-FDMA systems. The proposed algorithm is based on low-complexity estimation for the partial solution space. Compared with existing algorithms, simulation results show that our algorithm improves the system utility significantly and has less deviation to global optimum. In addition, the proposed algorithm framework allows a flexible trade-off between computational effort and solution performance by varying the complexity of estimation approaches.

The 4G standard Long Term Evolution (LTE) has been developed for high-bandwidth mobile access for today's data-heavy applications, consequently, a better experience for the end user. To extend the user equipment battery lifetime, plus further support various services and large amount of data transmissions, the 3GPP standards for LTE/LTE-Advanced has adopted discontinuous reception (DRX). However, there is a need to optimize the DRX parameters, so as to maximize power saving without incurring network re-entry and packet delays. In this paper, we take an overview of the fixed frame DRX cycle and compare it against an adjustable DRX cycle of the LTE/LTE-Advanced power saving mechanism, by modelling the system with bursty packet data traffic using a semi-Markov process. Based on the analytical model, we will show the trade-off relationship between the power saving and wake-up delay performance.

As smartphone clients are restricted in computational power and bandwidth it is important to minimise the overhead of transmitted messages and since it results in processing time when implementing a web service. This paper identifies and studies methods that reduce the amount of data being transferred via wireless links between a Web service client and a Web service. The goal is to improve the end-to-end service execution time by reducing the bottleneck presented by the limited bandwidth in an ubiquitous environment. Measurements are performed in a real environment based on a web service prototype providing public transport information for the city of Hamburg in Germany, using actual wireless links with a mobile smartphone device. The existing SOAP based web service is evaluated against a REST based web service using the data exchange formats JSON, XML and Fast Infoset., ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Katrin Hameseder, Scott Fowler and Anders Peterson, Performance Analysis of Ubiquitous Web Systems for SmartPhones, 2011, IEEE International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS’11)., Swedish Excellence Center at Linkoping - Lund in information Technology (ELLIIT)

Long Term Evolution (LTE) of 3GPP provides high bandwidth for data transfer. Having high bandwidth transfer will exhaust the user equipment (UE)'s battery power quickly. To extend the UE's battery lifetime the 3GPP standards for LTE support Enhanced Discontinuous Reception (DRX). The DRX allow an idle UE to save battery by turning off the radio receiver for a predefined period. Since the Transmission Time Interval (TTI) is related to the size of the data block passed from the higher networks layers to the radio link layer, the DRX scheduler should vary the resource allocation of each user basis on TTI. In this paper, we have evaluated the influences of the TTI sizes as well as the effects of LTE DRX Light and Deep Sleep mode on power consumption for Voice and Web traffic., ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Scott Fowler , Study on Power Saving Based on Radio Frame in LTE Wireless Communication System Using DRX, 2011, IEEE Globecom Workshop on Workshop of SCPA and SaCoNAS., Swedish Excellence Center at Linkoping - Lund in information Technology (ELLIIT)