Graph Intersection-Based Benchmarking Algorithm for Maximum Stability Data Gathering Trees in Wireless Mobile Sensor Networks

The authors propose a graph intersection-based benchmarking algorithm to determine the sequence of longest-living stable data gathering trees for wireless mobile sensor networks whose topology changes dynamically with time due to the random movement of the sensor nodes. Referred to as the Maximum Stability-based Data Gathering (Max.Stable-DG) algorithm, the algorithm assumes the availability of complete knowledge of future topology changes and is based on the following greedy principle coupled with the idea of graph intersections: Whenever a new data gathering tree is required at time instant t corresponding to a round of data aggregation, choose the longest-living data gathering tree from time t. The above strategy is repeated for subsequent rounds over the lifetime of the sensor network to obtain the sequence of longest-living stable data gathering trees spanning all the live sensor nodes in the network such that the number of tree discoveries is the global minimum. In addition to theoretically proving the correctness of the Max.Stable-DG algorithm (that it yields the lower bound for the number of discoveries for any network-wide communication topology like spanning trees), the authors also conduct exhaustive simulations to evaluate the performance of the Max.Stable-DG trees and compare to that of the minimum-distance spanning tree-based data gathering trees with respect to metrics such as tree lifetime, delay per round, node lifetime and network lifetime, under both sufficient-energy and energy-constrained scenarios.

A Survey of MAC Layer Protocols to Avoid Deafness in Wireless Networks Using Directional Antenna

Directional antennas have gained immense popularity among researchers working in the area of wireless networks. These antennas help in enhancing the performance of wireless networks through increased spatial reuse, extended communication range, energy efficiency, reduced latency, and communication reliability. Traditional Medium Access Control (MAC) protocols such as IEEE 802.11 are designed based on use of omnidirectional antennas. Therefore, suitable design changes are required to exploit the benefits of directional antennas in wireless networks. Though directional antennas provide many benefits to enhance network performance, their inclusion in the network also results in certain challenges in network operation. Deafness is one such problem that occurs among nodes using directional antennas. This chapter concentrates on the problem of deafness, which is introduced due to the use of directional antennas in wireless ad-hoc, sensor, and mesh networks. Many researchers have provided numerous solutions to deal with the problem of deafness in these networks. In this chapter, the authors first explain the problem of deafness and then present an extensive survey of solutions available in the literature to deal with the problem of deafness in wireless ad-hoc, sensor, and mesh networks. The survey is accompanied by a critical analysis and comparison of available solutions. Drawbacks of available solutions are discussed and future research directions are presented.

Algorithms to Determine Stable Connected Dominating Sets for Mobile Ad Hoc Networks

This chapter presents three algorithms to determine stable connected dominating sets (CDS) for wireless mobile ad hoc networks (MANETs) whose topology changes dynamically with time. The three stability-based CDS algorithms are (1) Minimum Velocity (MinV)-based algorithm, which prefers to include a slow moving node as part of the CDS as long as it covers one uncovered neighbor node; (2) Node Stability Index (NSI)-based algorithm, which characterizes the stability of a node as the sum of the predicted expiration times of the links (LET) with its uncovered neighbor nodes, the nodes preferred for inclusion to the CDS in the decreasing order of their NSI values; (3) Strong Neighborhood (SN)-based algorithm, which prefers to include nodes that cover the maximum number of uncovered neighbors within its strong neighborhood (region identified by the Threshold Neighborhood Ratio and the fixed transmission range of the nodes). The three CDS algorithms have been designed to capture the node size—lifetime tradeoff at various levels. In addition to presenting a detailed description of the three stability-based CDS algorithms with illustrative examples, the authors present an exhaustive simulation study of these algorithms and compare their performance with respect to several metrics vis-à-vis an unstable maximum density-based MaxD-CDS algorithm that serves as the benchmark for the minimum CDS Node Size.

Mobility Prediction in Long Term Evolution (LTE) Femtocell Network

The Long Term Evolution (LTE) femtocell has promised to improve indoor coverage and enhance data rate capacity. Due to the special characteristic of the femtocell, it introduces several challenges in terms of mobility and interference management. This chapter focuses on mobility prediction in a wireless network in order to enhance handover performance. The mobility prediction technique via Markov Chains and a user’s mobility history is proposed as a technique to predict user movement in the deployment of the LTE femtocell. Simulations have been developed to evaluate the relationship between prediction accuracy and the amount of non-random data, as well as the relationship between the prediction accuracy and the duration of the simulation. The result shows that the prediction is more accurate if the user moves in regular mode, which is directly proportional to the amount of non-random data. Moreover, the prediction accuracy is maintained at 0.7 when the number of weeks is larger than 50.

Sustainable Growth for Cellular Wireless Networks

It has been widely recognised that the exchange of information is one of the underpinning factors for economic growth in developing and developed nations. One of the fastest growing areas of information transfer is the mobile data sector. In 2012, global mobile data traffic grew by 70%. There is an urgent need to improve the wireless capacity of cellular networks in order to match this growth. One of the key issues faced by mobile operators is the fall in Average Revenue Per User (ARPU) and the growing Operational Expenditure (OPEX) due to capacity growth and rising energy prices. The challenge is therefore how to grow the wireless capacity in a way that minimizes the OPEX and thus improves the ARPU. Furthermore, there is growing focus on the environmental impact of Information and Communication Technology (ICT) sectors. There are tangible, financial, and environmental motivations for reducing the energy expenditure of wireless networks whilst growing its capacity. This chapter examines recent research in the area of future wireless network architectures and deployments. This is done in the context of improving capacity in a sustainable way. That is to say, what is the lowest-cost and -energy method of achieving certain capacity targets? The authors of this chapter were researchers in the world’s first green wireless communications project—Mobile VCE Green Radio (2007-2012).

Metamaterial-Based Wearable Microstrip Patch Antennas

This chapter presents metamaterial-based wearable, that is, textile-based, antennas for Wi-Fi, WLAN, ISM, BAN and public safety band applications, which have been designed, fabricated, and tested. Textile substrates like polyester and polypropylene are used to design and fabricate these antennas. The metamaterial inclusions are directly used to load the different microstrip patch antennas on the same substrate, which significantly enhances the gain and bandwidth with considerable size reduction. The microstrip patch antenna generates sub-wavelength resonances under loading condition due to the modifications of its resonant modes. The DNG and SNG metamaterials are used to load the microstrip patch antennas for size reduction by generating the sub-wavelength resonances. The simulated and measured results are found to be in good agreement for all the presented wearable antennas. The bending effect on antenna performance due to human body movements is also presented in this chapter.

The Access of Things

Access to resources, both physical and cyber, must be controlled to maintain security. The increasingly connected nature of our world makes access control a paramount issue. The expansion of the Internet of Things into everyday life has created numerous opportunities to share information and resources with other people and other devices. The Internet of Things will contain numerous wireless devices. The level of access each user (human or device) is given must be controlled. Most conventional access control schemes are rigid in that they do not account for environmental context. This solution is not sufficient for the Internet of Things. What is needed is a more granular control of access rights and a gradual degradation or expansion of access based on observed facts. This chapter presents an access control system termed the Access of Things, which employs a gradual degradation of privilege philosophy. The Access of Things concept is applicable to the dynamic security environment present in the Internet of Things.

Transport Protocol Performance for Multi-Hop Transmission in Wireless Sensor Network (WSN)

The need for reliable data delivery at the transport layer for video transmission over IEEE 802.15.4 Wireless Sensor Networks (WSNs) has attracted great attention from the research community due to the applicability of multimedia transmission for many applications. The IEEE 802.15.4 standard is designed to transmit data within a network at a low rate and a short distance. However, the characteristics of WSNs such as dense deployment, limited processing ability, memory, and power supply provide unique challenges to transport protocol designers. Additionally, multimedia applications add further challenges such as requiring large bandwidth, large memory, and high data rate. This chapter discusses the challenges and evaluates the feasibility of transmitting data over an IEEE 802.15.4 network for different transport protocols. The analysis result highlights the comparison of standard transport protocols, namely User Datagram Protocol (UDP), Transport Control Protocol (TCP), and Stream Control Transmission Protocol (SCTP). The performance metrics are analyzed in terms of the packet delivery ratio, energy consumption, and end-to-end delay. Based on the study and analysis that has been done, the standard transport protocol can be modified and improved for multimedia data transmission in WSN. As a conclusion, SCTP shows significant improvement up to 18.635% and 40.19% for delivery ratio compared to TCP and UDP, respectively.

Self-Organization Activities in LTE-Advanced Networks

A major challenge in the context of LTE networks is a cost-effective network operation, which can be done by carefully controlling the network Operational Expenses (OPEX). Therefore, to minimize OPEX costs while optimizing network performance, Self-Organizing Network (SON) principles were proposed. These networks are the main focus of this chapter, which highlights the state of art and provides a comprehensive investigation of current research efforts in the field of SONs. A major contribution of the chapter is the handling of SON use cases, going through their challenges, solutions. and open research questions. The chapter also presents efforts to provide coordination frameworks between SON use cases and routines. An additional essential contribution of the chapter is the description of SON activities within 3GPP.

Evolution of Wireless and Mobile Communications

There has been a tremendous growth of mobile communications markets all over the world, as they provide ubiquitous communication access to citizens. Wireless technologies are the core of mobile communications. They fundamentally revolutionize data networking, telecommunication, and make integrated networks to increase capacity and coverage. This has made the network portable because of affordable digital modulation, adaptive modulation, information compression, wireless access, multiplexing, and so on. It supports exciting applications such as sensor networks, smart homes, telemedicine, video conferencing and distance learning, cognitive radio networks, automation, and so on. This chapter provides an overview of the evolution of wireless and mobile communications from 2G to 4G.