Network coding-aided MAC protocols for cooperative wireless networks

The introduction of third generation (3G) technologies has caused a vast proliferation of wireless devices and networks, generating an increasing demand for high level Quality of Service (QoS). The wide spread of mobile applications has further reinforced the user need for communication, motivating at the same time the concepts of user cooperation and data dissemination. However, this trend towards continuous exchange of information and ubiquitous connectivity is inherently restricted by the energy-greedy functionalities of high-end devices. These limitations, along with the pressure exerted on the Information and Communications Technology (ICT) industry towards energy awareness, have induced the design of novel energy efficient schemes and algorithms. In this context, the Medium Access Control (MAC) layer plays a key role, since it is mainly responsible for the channel access regulation, the transmission scheduling and the resource allocation, thus constituting an appropriate point to effectively address energy efficiency issues that arise due to the users overcrowding. This dissertation provides a contribution to the design, analysis and evaluation of novel MAC protocols for cooperative wireless networks. In our attempt to design energy efficient MAC schemes, we were extensively assisted by the introduction of new techniques, such as Network Coding (NC), that intrinsically bring considerable gains in system performance. The main thesis contributions are divided into two parts. The first part presents NCCARQ, a novel NC-aided Cooperative Automatic Repeat reQuest (ARQ) MAC protocol for wireless networks. NCCARQ introduces a new access paradigm for cooperative ARQ schemes, exploiting NC benefits in bidirectional communication among wireless users. The NCCARQ performance in terms of QoS and energy efficiency is assessed by means of analytical probabilistic models and extensive computer-based simulations, revealing the significant gains we can achieve compared to standardized MAC solutions. In addition, the impact of realistic wireless channel conditions on the MAC protocol operation further motivated us to study the NCCARQ performance in wireless links affected by correlated shadowing, showing that the channel correlation may adversely affect the distributed cooperation benefits. The second part of the thesis is dedicated to the investigation of MAC issues in wireless data dissemination scenarios. In particular, the existence of multiple source nodes in such scenarios generates conflicting situations, considering the selfish behavior of the wireless devices that want to maximize their battery lifetime. Bearing in mind the energy efficiency importance, we propose game theoretic medium access strategies, applying energy-based utility functions which inherently imply energy awareness. In addition, Random Linear NC (RLNC) techniques are adopted to eliminate the need of exchanging excessive control packets, while Analog NC (ANC) is employed to efface the impact of collisions throughout the communication. During the elaboration of this thesis, two general key conclusions have been extracted. First, there is a fundamental requirement for implementation of new MAC protocols in order to effectively deal with state-of-the-art techniques (e.g., NC), recently introduced to enhance both the performance and the energy efficiency of the network. Second, we highlight the importance of designing novel energy efficient MAC protocols, taking into account that traditional approaches - designed mainly to assist the collision avoidance in wireless networks - tend to be obsolete.La presente tesis doctoral contribuye al diseño, análisis y evaluación de nuevos protocolos MAC cooperativos para redes inalámbricas. La introducción de nuevas técnicas, tales como la codificación de red (NC), que intrínsecamente llevan un considerable aumento en el rendimiento del sistema, nos ayudó ampliamente durante el diseño de protocolos MAC energéticamente eficientes. Las principales contribuciones de esta tesis se dividen en dos partes. La primera parte presenta el NCCARQ, un protocolo cooperativo de retransmisión automática (ARQ), asistido por NC para redes inalámbricas. La segunda parte de la tesis se centra en el diseño de protocolos de capa MAC en escenarios inalámbricos de difusión de datos. Teniendo en cuenta la importancia de la eficiencia energética, se proponen técnicas de acceso al medio basadas en teoría de juegos dónde las funciones objetivo están motivadas por el consumo energético. Las soluciones propuestas son evaluadas por medio de modelos analíticos y simulaciones por ordenador

Optimal Design of Wireless Sensor Networks

Since their introduction,Wireless SensorNetworks(WSN) have been proposed as a powerful support for environment monitoring, ranging from monitoring of remote or hard-to-reach locations to fine-grained control of cultivations. Development of a WSN-based application is a complex task and challenging issues must be tackled starting from the first phases of the design cycle.We present here a tool supporting the DSE phase to perform architectural choices for the nodes and network topology, taking into account target performance goals and estimated costs. When designing applications based onWSN, the most challenging problem is energy shortage. Nodes are normally supplied through batteries, hence a limited amount of energy is available and no breakthroughs are foreseen in a near future. In our design cycle we approach this issue through a methodology that allows analysing and optimising the power performances in a hierarchical fashion, encompassing various abstraction levels

An Evaluation of Performance Enhancements to Particle Swarm Optimisation on Real-World Data

Swarm Computation is a relatively new optimisation paradigm. The basic premise is to model the collective behaviour of self-organised natural phenomena such as swarms, flocks and shoals, in order to solve optimisation problems. Particle Swarm Optimisation (PSO) is a type of swarm computation inspired by bird flocks or swarms of bees by modelling their collective social influence as they search for optimal solutions. In many real-world applications of PSO, the algorithm is used as a data pre-processor for a neural network or similar post processing system, and is often extensively modified to suit the application. The thesis introduces techniques that allow unmodified PSO to be applied successfully to a range of problems, specifically three extensions to the basic PSO algorithm: solving optimisation problems by training a hyperspatial matrix, using a hierarchy of swarms to coordinate optimisation on several data sets simultaneously, and dynamic neighbourhood selection in swarms. Rather than working directly with candidate solutions to an optimisation problem, the PSO algorithm is adapted to train a matrix of weights, to produce a solution to the problem from the inputs. The search space is abstracted from the problem data. A single PSO swarm optimises a single data set and has difficulties where the data set comprises disjoint parts (such as time series data for different days). To address this problem, we introduce a hierarchy of swarms, where each child swarm optimises one section of the data set whose gbest particle is a member of the swarm above in the hierarchy. The parent swarm(s) coordinate their children and encourage more exploration of the solution space. We show that hierarchical swarms of this type perform better than single swarm PSO optimisers on the disjoint data sets used. PSO relies on interaction between particles within a neighbourhood to find good solutions. In many PSO variants, possible interactions are arbitrary and fixed on initialisation. Our third contribution is a dynamic neighbourhood selection: particles can modify their neighbourhood, based on the success of the candidate neighbour particle. As PSO is intended to reflect the social interaction of agents, this change significantly increases the ability of the swarm to find optimal solutions. Applied to real-world medical and cosmological data, this modification is and shows improvements over standard PSO approaches with fixed neighbourhoods

Energy Efficient and Secure Wireless Sensor Networks Design

Wireless Sensor Networks (WSNs) are emerging technologies that have the ability to sense, process, communicate, and transmit information to a destination, and they are expected to have significant impact on the efficiency of many applications in various fields. The resource constraint such as limited battery power, is the greatest challenge in WSNs design as it affects the lifetime and performance of the network. An energy efficient, secure, and trustworthy system is vital when a WSN involves highly sensitive information. Thus, it is critical to design mechanisms that are energy efficient and secure while at the same time maintaining the desired level of quality of service. Inspired by these challenges, this dissertation is dedicated to exploiting optimization and game theoretic approaches/solutions to handle several important issues in WSN communication, including energy efficiency, latency, congestion, dynamic traffic load, and security. We present several novel mechanisms to improve the security and energy efficiency of WSNs. Two new schemes are proposed for the network layer stack to achieve the following: (a) to enhance energy efficiency through optimized sleep intervals, that also considers the underlying dynamic traffic load and (b) to develop the routing protocol in order to handle wasted energy, congestion, and clustering. We also propose efficient routing and energy-efficient clustering algorithms based on optimization and game theory. Furthermore, we propose a dynamic game theoretic framework (i.e., hyper defense) to analyze the interactions between attacker and defender as a non-cooperative security game that considers the resource limitation. All the proposed schemes are validated by extensive experimental analyses, obtained by running simulations depicting various situations in WSNs in order to represent real-world scenarios as realistically as possible. The results show that the proposed schemes achieve high performance in different terms, such as network lifetime, compared with the state-of-the-art schemes

Channel Access Management in Data Intensive Sensor Networks

There are considerable challenges for channel access in Data Intensive Sensor Networks - DISN, supporting Data Intensive Applications like Structural Health Monitoring. As the data load increases, considerable degradation of the key performance parameters of such sensor networks is observed. Successful packet delivery ratio drops due to frequent collisions and retransmissions. The data glut results in increased latency and energy consumption overall. With the considerable limitations on sensor node resources like battery power, this implies that excessive transmissions in response to sensor queries can lead to premature network death. After a certain load threshold the performance characteristics of traditional WSNs become unacceptable. Research work indicates that successful packet delivery ratio in 802.15.4 networks can drop from 95% to 55% as the offered network load increases from 1 packet/sec to 10 packets/sec. This result in conjunction with the fact that it is common for sensors in an SHM system to generate 6-8 packets/sec of vibration data makes it important to design appropriate channel access schemes for such data intensive applications.In this work, we address the problem of significant performance degradation in a special-purpose DISN. Our specific focus is on the medium access control layer since it gives a fine-grained control on managing channel access and reducing energy waste. The goal of this dissertation is to design and evaluate a suite of channel access schemes that ensure graceful performance degradation in special-purpose DISNs as the network traffic load increases.First, we present a case study that investigates two distinct MAC proposals based on random access and scheduling access. The results of the case study provide the motivation to develop hybrid access schemes. Next, we introduce novel hybrid channel access protocols for DISNs ranging from a simple randomized transmission scheme that is robust under channel and topology dynamics to one that utilizes limited topological information about neighboring sensors to minimize collisions and energy waste. The protocols combine randomized transmission with heuristic scheduling to alleviate network performance degradation due to excessive collisions and retransmissions. We then propose a grid-based access scheduling protocol for a mobile DISN that is scalable and decentralized. The grid-based protocol efficiently handles sensor mobility with acceptable data loss and limited overhead. Finally, we extend the randomized transmission protocol from the hybrid approaches to develop an adaptable probability-based data transmission method. This work combines probabilistic transmission with heuristics, i.e., Latin Squares and a grid network, to tune transmission probabilities of sensors, thus meeting specific performance objectives in DISNs. We perform analytical evaluations and run simulation-based examinations to test all of the proposed protocols

Performance Enhancement of Multipath TCP for Wireless Communications with Multiple Radio Interfaces

ArticleMultipath TCP (MPTCP) allows a TCP connection to operate across multiple paths simultaneously and becomes highly attractive to support the emerging mobile devices with various radio interfaces and to improve resource utilization as well as connection robustness. The existing multipath congestion control algorithms, however, are mainly loss-based and prefer the paths with lower drop rates, leading to severe performance degradation in wireless communication systems where random packet losses occur frequently. To address this challenge, this paper proposes a new mVeno algorithm, which makes full use of the congestion information of all the subflows belonging to a TCP connection in order to adaptively adjust the transmission rate of each subflow. Specifically, mVeno modifies the additive increase phase of Veno so as to effectively couple all subflows by dynamically varying the congestion window increment based on the receiving ACKs. The weighted parameter of each subflow for tuning the congestio

Consensus-based Time Synchronization Algorithms for Wireless Sensor Networks with Topological Optimization Strategies for Performance Improvement

Wireless Sensor Networks(WSNs)have received considerable attention in recent years because of its broad area of applications.In the same breadth,it also faces many challenges.Time synchronization is one of those fundamental challenges faced by WSN being a distributed system.It is a service by which all nodes in the network will share a common notion of time.It is a prerequisite for correctness of other protocols and services like security,localization and tracking protocols.Several approaches have been proposed in the last decade for time synchronization in WSNs.The well-known methods are based on synchronizing to a reference(root)node's time by considering a hierarchical backbone for the network.However,this approach seems to be not purely distributed,higher accumulated synchronization error for the farthest node from the root and subjected to the root node failure problem.Recently,consensus based approaches are gaining popularity due its computational lightness,robustness, and distributed nature.In this thesis,average consensus-based time synchronization algorithms are proposed,aiming to improve the performance metrics like number of iterations for convergence,total synchronization error,local synchronization error,message complexity,and scalability.Further,to cope up with energy constraint environment, Genetic algorithm based topological optimization strategies are proposed to minimize energy consumption and to accelerate the consensus convergence of the existing consensus-based time synchronization algorithms.All algorithms are analyzed mathematically and validated through simulation in MATLAB based PROWLER simulator.Firstly,a distributed Selective Average Time Synchronization (SATS) algorithm is proposed based on average consensus theory.The algorithm is purely distributed(runs at each node),and each node exploits a selective averaging with the neighboring node having maximum clock difference. To identify the neighboring node with maximum clock difference,every node broadcasts a synchronization initiation message to the neighboring nodes at its local oscillation period and waits for a random interval to get the synchronization acknowledgment messages.After receiving acknowledgment messages,a node estimates relative clock value and sends an averaging message to the selected node.The iteration continues until all nodes reach an acceptable synchronization error bound. The optimal convergence of the proposed SATS algorithm is analyzed and validated through simulation and compared with some state-of-the-art,average consensus based time synchronization algorithms. Furthermore, it is observed that most of the consensus-based time synchronization algorithms are one-hop in nature, i.e., the algorithms iterate by averaging with one-hop neighbors' clock value. In a sparse network with a lower average degree of connectivity, these algorithms show poor performance. In order to have better convergence on the sparse network, a multi-hop SATS algorithm is proposed. The basic principle of multi-hop SATS algorithm remains same as that of SATS algorithm, i.e., performing selective averaging with the neighboring node, having maximum clock difference. But, in this case, the search for neighboring node goes beyond one hop. The major challenge lies in multi-hop search is the end-to-end delay which increases with the increase in hop count. So, to search a multi-hop neighboring node with maximum clock difference and with minimum and bounded end-to-end delay, a distributed, constraint-based dynamic programming approach is proposed for multi-hop SATS algorithm. The performance of the proposed multi-hop SATS algorithm is compared with some one-hop consensus time synchronization algorithms. Simulation results show notable improvement in terms of convergence speed, total synchronization error within a restricted hop count. The trade-off with the increase in number of hops is also studied. The well-known consensus-based time synchronization algorithms are ``all node based'', i.e., every node iterates the algorithm to reach the synchronized state. This increases the overall message complexity and consumption of energy. Further, congestion in the network increases due to extensive synchronization message exchanges and induces the delay in the network. The delay induced in the message exchange is the main source of synchronization error and slows down the convergence speed to the synchronized (consensus) state. Hence, it is desirable that a subset of sensors along with a reasonable number of neighboring sensors should be selected in such a way that the resultant logical topology will accelerate the consensus algorithm with optimal message complexity and minimizes energy consumption. This problem is formulated as topological optimization problem which is claimed to be NP-complete in nature. Therefore, Genetic Algorithm (GA) based approaches are used to tackle this problem. Considering dense network topology, a single objective GA-based approach is proposed and considering sparse topology, a multi-objective Random Weighted GA based approach is proposed. Using the proposed topological optimization strategy, significant improvements are observed for consensus-based time synchronization algorithms in terms of average number of messages exchanged, energy consumption, and average mean square synchronization error

Design Space Exploration and Resource Management of Multi/Many-Core Systems

The increasing demand of processing a higher number of applications and related data on computing platforms has resulted in reliance on multi-/many-core chips as they facilitate parallel processing. However, there is a desire for these platforms to be energy-efficient and reliable, and they need to perform secure computations for the interest of the whole community. This book provides perspectives on the aforementioned aspects from leading researchers in terms of state-of-the-art contributions and upcoming trends