Cross-layer design of multi-hop wireless networks

MULTI -hop wireless networks are usually defined as a collection of nodes equipped with radio transmitters, which not only have the capability to communicate each other in a multi-hop fashion, but also to route each others’ data packets. The distributed nature of such networks makes them suitable for a variety of applications where there are no assumed reliable central entities, or controllers, and may significantly improve the scalability issues of conventional single-hop wireless networks. This Ph.D. dissertation mainly investigates two aspects of the research issues related to the efficient multi-hop wireless networks design, namely: (a) network protocols and (b) network management, both in cross-layer design paradigms to ensure the notion of service quality, such as quality of service (QoS) in wireless mesh networks (WMNs) for backhaul applications and quality of information (QoI) in wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of this Ph.D. dissertation, different network settings are used as illustrative examples, however the proposed algorithms, methodologies, protocols, and models are not restricted in the considered networks, but rather have wide applicability. First, this dissertation proposes a cross-layer design framework integrating a distributed proportional-fair scheduler and a QoS routing algorithm, while using WMNs as an illustrative example. The proposed approach has significant performance gain compared with other network protocols. Second, this dissertation proposes a generic admission control methodology for any packet network, wired and wireless, by modeling the network as a black box, and using a generic mathematical 0. Abstract 3 function and Taylor expansion to capture the admission impact. Third, this dissertation further enhances the previous designs by proposing a negotiation process, to bridge the applications’ service quality demands and the resource management, while using WSNs as an illustrative example. This approach allows the negotiation among different service classes and WSN resource allocations to reach the optimal operational status. Finally, the guarantees of the service quality are extended to the environment of multiple, disconnected, mobile subnetworks, where the question of how to maintain communications using dynamically controlled, unmanned data ferries is investigated

Review of Optimization Problems in Wireless Sensor Networks

International audienc

Resource Allocation in Ad Hoc Networks

Unlike the centralized network, the ad hoc network does not have any central administrations and energy is constrained, e.g. battery, so the resource allocation plays a very important role in efficiently managing the limited energy in ad hoc networks. This thesis focuses on the resource allocation in ad hoc networks and aims to develop novel techniques that will improve the network performance from different network layers, such as the physical layer, Medium Access Control (MAC) layer and network layer. This thesis examines the energy utilization in High Speed Downlink Packet Access (HSDPA) systems at the physical layer. Two resource allocation techniques, known as channel adaptive HSDPA and two-group HSDPA, are developed to improve the performance of an ad hoc radio system through reducing the residual energy, which in turn, should improve the data rate in HSDPA systems. The channel adaptive HSDPA removes the constraint on the number of channels used for transmissions. The two-group allocation minimizes the residual energy in HSDPA systems and therefore enhances the physical data rates in transmissions due to adaptive modulations. These proposed approaches provide better data rate than rates achieved with the current HSDPA type of algorithm. By considering both physical transmission power and data rates for defining the cost function of the routing scheme, an energy-aware routing scheme is proposed in order to find the routing path with the least energy consumption. By focusing on the routing paths with low energy consumption, computational complexity is significantly reduced. The data rate enhancement achieved by two-group resource allocation further reduces the required amount of energy per bit for each path. With a novel load balancing technique, the information bits can be allocated to each path in such that a way the overall amount of energy consumed is minimized. After loading bits to multiple routing paths, an end-to-end delay minimization solution along a routing path is developed through studying MAC distributed coordination function (DCF) service time. Furthermore, the overhead effect and the related throughput reduction are studied. In order to enhance the network throughput at the MAC layer, two MAC DCF-based adaptive payload allocation approaches are developed through introducing Lagrange optimization and studying equal data transmission period

Joint optimization for wireless sensor networks in critical infrastructures

Energy optimization represents one of the main goals in wireless sensor network design where a typical sensor node has usually operated by making use of the battery with limited-capacity. In this thesis, the following main problems are addressed: first, the joint optimization of the energy consumption and the delay for conventional wireless sensor networks is presented. Second, the joint optimization of the information quality and energy consumption of the wireless sensor networks based structural health monitoring is outlined. Finally, the multi-objectives optimization of the former problem under several constraints is shown. In the first main problem, the following points are presented: we introduce a joint multi-objective optimization formulation for both energy and delay for most sensor nodes in various applications. Then, we present the Karush-Kuhn-Tucker analysis to demonstrate the optimal solution for each formulation. We introduce a method of determining the knee on the Pareto front curve, which meets the network designer interest for focusing on more practical solutions. The sensor node placement optimization has a significant role in wireless sensor networks, especially in structural health monitoring. In the second main problem of this work, the existing work optimizes the node placement and routing separately (by performing routing after carrying out the node placement). However, this approach does not guarantee the optimality of the overall solution. A joint optimization of sensor placement, routing, and flow assignment is introduced and is solved using mixed-integer programming modelling. In the third main problem of this study, we revisit the placement problem in wireless sensor networks of structural health monitoring by using multi-objective optimization. Furthermore, we take into consideration more constraints that were not taken into account before. This includes the maximum capacity per link and the node-disjoint routing. Since maximum capacity constraint is essential to study the data delivery over limited-capacity wireless links, node-disjoint routing is necessary to achieve load balancing and longer wireless sensor networks lifetime. We list the results of the previous problems, and then we evaluate the corresponding results

A survey of network lifetime maximization techniques in wireless sensor networks

Emerging technologies, such as the Internet of things, smart applications, smart grids and machine-to-machine networks stimulate the deployment of autonomous, selfconfiguring, large-scale wireless sensor networks (WSNs). Efficient energy utilization is crucially important in order to maintain a fully operational network for the longest period of time possible. Therefore, network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance in terms of extending the flawless operation of battery-constrained WSNs. In this paper, we review the recent developments in WSNs, including their applications, design constraints and lifetime estimation models. Commencing with the portrayal of rich variety definitions of NL design objective used for WSNs, the family of NL maximization techniques is introduced and some design guidelines with examples are provided to show the potential improvements of the different design criteri

Survey: energy efficient protocols using radio scheduling in wireless sensor network

An efficient energy management scheme is crucial factor for design and implementation of any sensor network. Almost all sensor networks are structured with numerous small sized, low cost sensor devices which are scattered over the large area. To improvise the network performance by high throughput with minimum energy consumption, an energy efficient radio scheduling MAC protocol is effective solution, since MAC layer has the capability to collaborate with distributed wireless networks. The present survey study provides relevant research work towards radio scheduling mechanism in the design of energy efficient wireless sensor networks (WSNs). The various radio scheduling protocols are exist in the literature, which has some limitations. Therefore, it is require developing a new energy efficient radio scheduling protocol to perform multi tasks with minimum energy consumption (e.g. data transmission). The most of research studies paying more attention towards to enhance the overall network lifetime with the aim of using energy efficient scheduling protocol. In that context, this survey study overviews the different categories of MAC based radio scheduling protocols and those protocols are measured by evaluating their data transmission capability, energy efficiency, and network performance. With the extensive analysis of existing works, many research challenges are stated. Also provides future directions for new WSN design at the end of this survey

Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing in Wireless Sensor Networks

There are many challenges when designing and deploying wireless sensor networks (WSNs). One of the key challenges is how to make full use of the limited energy to prolong the lifetime of the network, because energy is a valuable resource in WSNs. The status of energy consumption should be continuously monitored after network deployment. In this paper, we propose coverage and connectivity aware neural network based energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with coverage and connectivity aware constraints. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage and connectivity aware routing with data transmission. The proposed scheme is compared with existing schemes with respect to the parameters such as number of alive nodes, packet delivery fraction, and node residual energy. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.Comment: 16 Pages, JGraph-Hoc Journa

Sustainable optimizing WMN performance through meta-heuristic TDMA link scheduling and routing

Wireless mesh networks (WMNs) have become a popular solution for expanding internet service and communication in both urban and rural areas. However, the performance of WMNs depends on generating optimized time-division multiple access (TDMA) schedules, which distribute time into a list of slots called superframes. This study proposes novel meta-heuristic algorithms to generate TDMA link schedules in WMNs using two different interference/constraint models: multi-transmit-receive (MTR) and full-duplex (FD). The objectives of this study are to optimize the TDMA frame for packet transmission, satisfy the constraints, and minimize the end-to-end delay. The significant contributions of this study are: (1) proposing effective and efficient heuristic solutions to solve the NP-complete problem of generating optimal TDMA link schedules in WMNs; (2) investigating the new FD interference model to improve the network capacity above the physical layer. To achieve these objectives and contributions, the study uses two popular meta-heuristics, the artificial bee colony (ABC) and/or genetic algorithm (GA), to solve the known NP-complete problems of joint scheduling, power control, and rate control. The results of this study show that the proposed algorithms can generate optimized TDMA link schedules for both MTR and FD models. The joint routing and scheduling approach further minimizes end-to-end delay while maintaining the schedule's minimum length and/or maximum capacity. The proposed solution outperforms the existing solutions in terms of the number of active links, end-to-end delay, and network capacity. The research aims to improve the efficiency and effectiveness of WMNs in most applications that require high throughput and fast response time