Energy Efficient Communication Protocols for Wireless Sensor Networks

The popularity of Wireless Sensor Networks have increased tremendously due to the vast potential of the sensor networks to connect the physical world with the virtual world. Since these devices rely on battery power and may be placed in hostile environments replacing them becomes a tedious task. Thus, improving the energy of these networks becomes important.The thesis provides methods for clustering and cluster head selection to WSN to improve energy efficiency. It presents a comparison between the different methods on the basis of the network lifetime . It proposes a modified approach for cluster head selection with good performance and reduced computational complexity .In addition it also proposes BFO as an algorithm for clustering of WSN which would result improved performance with faster convergence

Initialization algorithms for wireless ad-hoc networks

The aim of this master thesis is the implementation of simulation models and the simulation of energy-efficient network initialization algorithms. First of all, it is presented a survey of state-of-the-art strategies for network initialization and exploration in wireless ad-hoc networks. Among the routing approaches presented in the survey it has been chosen the clustering-based approach due to it is the most suitable for ad-hoc sensor networks. Following are explained the features and properties of the clustering-based routing algorithms that have been selected for their implementation on this work. These implemented routing protocols are LEACH, LEACH-C, the solaraware extensions of both, HEED and a protocol based on direct transmission just as a reference in the comparison among the rest of them. On the other hand, all these routing protocols have been implemented and simulated using the OMNeT++ 4.0, which is a freeware discrete simulation environment. Subsequently, all the protocols have been simulated with different parameters and conditions to prove their functionality and to find out their behaviour in different sorts of sensor networks. Next, the simulations of the algorithms are compared among each other especially in terms of communication and energy efficiency. There are presented different comparisons such as LEACH and LEACH-C with their respective solar-aware extensions of both, a comparison between HEED with optimized parameters and non-optimized parameters, and finally a general comparison among One-hop, LEACH, LEACH-C and HEED. To sum up, some conclusions are drawn about the performance of the different protocols and some key points are given for future work. Furthermore, it is presented a brief study of the environmental impact this work may have

PERFORMANCE ANALYSIS AND OPTIMIZATION OF QUERY-BASED WIRELESS SENSOR NETWORKS

This dissertation is concerned with the modeling, analysis, and optimization of large-scale, query-based wireless sensor networks (WSNs). It addresses issues related to the time sensitivity of information retrieval and dissemination, network lifetime maximization, and optimal clustering of sensor nodes in mobile WSNs. First, a queueing-theoretic framework is proposed to evaluate the performance of such networks whose nodes detect and advertise significant events that are useful for only a limited time; queries generated by sensor nodes are also time-limited. The main performance parameter is the steady state proportion of generated queries that fail to be answered on time. A scalable approximation for this parameter is first derived assuming the transmission range of sensors is unlimited. Subsequently, the proportion of failed queries is approximated using a finite transmission range. The latter approximation is remarkably accurate, even when key model assumptions related to event and query lifetime distributions and network topology are violated. Second, optimization models are proposed to maximize the lifetime of a query-based WSN by selecting the transmission range for all of the sensor nodes, the resource replication level (or time-to-live counter) and the active/sleep schedule of nodes, subject to connectivity and quality-of-service constraints. An improved lower bound is provided for the minimum transmission range needed to ensure no network nodes are isolated with high probability. The optimization models select the optimal operating parameters in each period of a finite planning horizon, and computational results indicate that the maximum lifetime can be significantly extended by adjusting the key operating parameters as sensors fail over time due to energy depletion. Finally, optimization models are proposed to maximize the demand coverage and minimize the costs of locating, and relocating, cluster heads in mobile WSNs. In these models, the locations of mobile sensor nodes evolve randomly so that each sensor must be optimally assigned to a cluster head during each period of a finite planning horizon. Additionally, these models prescribe the optimal times at which to update the sensor locations to improve coverage. Computational experiments illustrate the usefulness of dynamically updating cluster head locations and sensor location information over time

BATSEN: Modifying the BATMAN Routing Protocol for Wireless Sensor Networks

The proliferation of autonomous Wireless Sensor Networks (WSN) has spawned research seeking power efficient communications to improve the lifetime of sensor motes. WSNs are characterized by their power limitations, wireless transceivers, and the converge-cast communications techniques. WSN motes use low-power, lossy radio systems deployed in dense, random topologies, working sympathetically to sense and notify a sink node of the detectable information. In an effort to extend the life of battery powered motes, and hence the life of the network, various routing protocols have been suggested in an effort to optimize converge-cast delivery of sensor data. It is well known that reducing the overhead required to perform converge-cast routing and communications reduces the effects of the primary power drain in the mote, the transceiver. Furthermore, WSNs are not well protected; network security costs energy both in computation and in RF transmission. This paper investigates the use of a Mobile Ad-hoc Networking (MANET) routing protocol known as B.A.T.M.A.N. in WSN. This thesis proposes that the features of B.A.T.M.A.N. in the MANET realm may prove beneficial to the WSN routing domain; and that slight modifications to the routing technique may prove beneficial beyond current protocol technologies. The B.A.T.M.A.N. variant will be compared against the contemporary LEACH WSN routing protocol to discern any potential energy savings

ENERGY-EFFICIENT ROUTING ALGORITHMS FOR WIRELESS SENSOR NETWORKS

A wireless sensor network (WSN) is made of tiny sensor nodes usually deployed in high density within a targeted area to monitor a phenomenon of interest such as temperature, vibration or humidity. The WSNs can be employed in various applications (e.g., Structural monitoring, agriculture, environment monitoring, machine health monitoring, military, and health). For each application area there are different technical issues and remedies. Various challenges need to be considered while setting up a WSN, including limited computing, memory and energy resources, wireless channel errors and network scalability. One way of addressing these problems is by implementing a routing protocol that efficiently uses these limited resources and hence reduces errors, improves scalability and increases the network lifetime. The topology of any network is important and wireless sensor networks (WSNs) are no exception. In order to effectively model an energy-efficient routing algorithm, the topology of the WSN must be factored in. However, little work has been done on routing for WSNs with regular patterned topologies, except for the shortest path first (SPF) routing algorithms. The issue with the SPF algorithm is that it requires global location information of the nodes from the sensor network, which proves to be a drain on the network resources. In this thesis a novel algorithm namely, BRALB (Biased Random Algorithm for Load Balancing) is proposed to overcome the issues faced in routing data within WSNs with regular topologies such as square-base topology and triangle-based topology. It is based on random walk and probability. The proposed algorithm uses probability theory to build a repository of information containing the estimate of energy resources in each node, in order to route packets based on the energy resources in each node and thus does not require any global information from the network. It is shown in this thesis by statistical analysis and simulations that BRALB uses the same energy as the shortest path first routing as long as the data packets are comparable in size to the inquiry packets used between neighbours. It is also shown to balance the load (i.e. the packets to be sent) efficiently among the nodes in the network. In most of the WSN applications the messages sent to the base station are very small in size. Therefore BRALB is viable and can be used in sensor networks employed in such applications. However, one of the constraints of BRALB is that it is not very scalable; this is a genuine concern as most WSNs deployment is large scale.In order to remedy this problem, C-BRALB (Clustered Biased Random Algorithm for Load Balancing) has been proposed as an extension of BRALB with clustering mechanism. The same clustering technique used in Improved Directed Diffusion (IDD) has been adopted for C-BRALB. The routing mechanism in C-BRALB is based on energy biased random walk. This algorithm also does not require any global information apart from the initial flooding initiated by the sink to create the clusters. It uses probability theory to acquire all the information it needs to route packets based on energy resources in each cluster head node. It is shown in this thesis by using both simulations and statistical analysis that C-BRALB is an efficient routing algorithm in applications where the message to be sent is comparable to the inquiry message among the neighbours. It is also shown to balance the load (i.e. the packets to be sent) among the neighbouring cluster head nodes

Multiprocessor System-on-Chips based Wireless Sensor Network Energy Optimization

Wireless Sensor Network (WSN) is an integrated part of the Internet-of-Things (IoT) used to monitor the physical or environmental conditions without human intervention. In WSN one of the major challenges is energy consumption reduction both at the sensor nodes and network levels. High energy consumption not only causes an increased carbon footprint but also limits the lifetime (LT) of the network. Network-on-Chip (NoC) based Multiprocessor System-on-Chips (MPSoCs) are becoming the de-facto computing platform for computationally extensive real-time applications in IoT due to their high performance and exceptional quality-of-service. In this thesis a task scheduling problem is investigated using MPSoCs architecture for tasks with precedence and deadline constraints in order to minimize the processing energy consumption while guaranteeing the timing constraints. Moreover, energy-aware nodes clustering is also performed to reduce the transmission energy consumption of the sensor nodes. Three distinct problems for energy optimization are investigated given as follows: First, a contention-aware energy-efficient static scheduling using NoC based heterogeneous MPSoC is performed for real-time tasks with an individual deadline and precedence constraints. An offline meta-heuristic based contention-aware energy-efficient task scheduling is developed that performs task ordering, mapping, and voltage assignment in an integrated manner. Compared to state-of-the-art scheduling our proposed algorithm significantly improves the energy-efficiency. Second, an energy-aware scheduling is investigated for a set of tasks with precedence constraints deploying Voltage Frequency Island (VFI) based heterogeneous NoC-MPSoCs. A novel population based algorithm called ARSH-FATI is developed that can dynamically switch between explorative and exploitative search modes at run-time. ARSH-FATI performance is superior to the existing task schedulers developed for homogeneous VFI-NoC-MPSoCs. Third, the transmission energy consumption of the sensor nodes in WSN is reduced by developing ARSH-FATI based Cluster Head Selection (ARSH-FATI-CHS) algorithm integrated with a heuristic called Novel Ranked Based Clustering (NRC). In cluster formation parameters such as residual energy, distance parameters, and workload on CHs are considered to improve LT of the network. The results prove that ARSH-FATI-CHS outperforms other state-of-the-art clustering algorithms in terms of LT.University of Derby, Derby, U

Cross-layer energy optimisation of routing protocols in wireless sensor networks

Recent technological developments in embedded systems have led to the emergence of a new class of networks, known asWireless Sensor Networks (WSNs), where individual nodes cooperate wirelessly with each other with the goal of sensing and interacting with the environment.Many routing protocols have been developed tomeet the unique and challenging characteristics of WSNs (notably very limited power resources to sustain an expected lifetime of perhaps years, and the restricted computation, storage and communication capabilities of nodes that are nonetheless required to support large networks and diverse applications). No standards for routing have been developed yet for WSNs, nor has any protocol gained a dominant position among the research community. Routing has a significant influence on the overall WSN lifetime, and providing an energy efficient routing protocol remains an open problem. This thesis addresses the issue of designing WSN routing methods that feature energy efficiency. A common time reference across nodes is required in mostWSN applications. It is needed, for example, to time-stamp sensor samples and for duty cycling of nodes. Alsomany routing protocols require that nodes communicate according to some predefined schedule. However, independent distribution of the time information, without considering the routing algorithm schedule or network topology may lead to a failure of the synchronisation protocol. This was confirmed empirically, and was shown to result in loss of connectivity. This can be avoided by integrating the synchronisation service into the network layer with a so-called cross-layer approach. This approach introduces interactions between the layers of a conventional layered network stack, so that the routing layer may share information with other layers. I explore whether energy efficiency can be enhanced through the use of cross-layer optimisations and present three novel cross-layer routing algorithms. The first protocol, designed for hierarchical, cluster based networks and called CLEAR (Cross Layer Efficient Architecture for Routing), uses the routing algorithm to distribute time information which can be used for efficient duty cycling of nodes. The second method - called RISS (Routing Integrated Synchronization Service) - integrates time synchronization into the network layer and is designed to work well in flat, non-hierarchical network topologies. The third method - called SCALE (Smart Clustering Adapted LEACH) - addresses the influence of the intra-cluster topology on the energy dissipation of nodes. I also investigate the impact of the hop distance on network lifetime and propose a method of determining the optimal location of the relay node (the node through which data is routed in a two-hop network). I also address the problem of predicting the transition region (the zone separating the region where all packets can be received and that where no data can be received) and I describe a way of preventing the forwarding of packets through relays belonging in this transition region. I implemented and tested the performance of these solutions in simulations and also deployed these routing techniques on sensor nodes using TinyOS. I compared the average power consumption of the nodes and the precision of time synchronization with the corresponding parameters of a number of existing algorithms. All proposed schemes extend the network lifetime and due to their lightweight architecture they are very efficient on WSN nodes with constrained resources. Hence it is recommended that a cross-layer approach should be a feature of any routing algorithm for WSNs

A Review of Wireless Sensor Networks with Cognitive Radio Techniques and Applications

The advent of Wireless Sensor Networks (WSNs) has inspired various sciences and telecommunication with its applications, there is a growing demand for robust methodologies that can ensure extended lifetime. Sensor nodes are small equipment which may hold less electrical energy and preserve it until they reach the destination of the network. The main concern is supposed to carry out sensor routing process along with transferring information. Choosing the best route for transmission in a sensor node is necessary to reach the destination and conserve energy. Clustering in the network is considered to be an effective method for gathering of data and routing through the nodes in wireless sensor networks. The primary requirement is to extend network lifetime by minimizing the consumption of energy. Further integrating cognitive radio technique into sensor networks, that can make smart choices based on knowledge acquisition, reasoning, and information sharing may support the network's complete purposes amid the presence of several limitations and optimal targets. This examination focuses on routing and clustering using metaheuristic techniques and machine learning because these characteristics have a detrimental impact on cognitive radio wireless sensor node lifetime