Overlapping layers for prolonging network life time in multi-hop wireless sensor networks

Wireless sensor networks have been proposed as a practical solution for a wide range of applications due to their benefits of low cost, rapid deployment, self-organization capability, and cooperative data-processing. Many applications, such as military surveillance and habitat monitoring, require the deployment of large-scale sensor networks. A highly scalable and fault-tolerant network architecture, the Progressive Multi-hop Rotational Clustered (PMRC) structure has been proposed, which is suitable for constructing large-scale wireless sensor networks. However, similar to other multi-hop structures, the PMRC structure also suffers from the bottleneck problem; This thesis is focused on solving the bottleneck problem existing in the PMRC structure. First, the Overlapping Neighbor Layers (ONL) scheme is proposed to balance the energy consumption among cluster heads at different layers. Further, the Minimum Overlapping Neighbor Layers (MONL) scheme is proposed wherein the overlapped area between neighbor layers is gradually increased through network life time to achieve load balance and energy efficiency in the whole network area. Simulation results show that the MONL scheme significantly prolongs network life time and demonstrates steady performance on sensor networks with uniformly distributed sensor nodes. To further prolong the network life time, traffic-similar sensor nodes distribution combined with the MONL scheme is studied; The proposed overlapped layers schemes are proven to be effective in solving the bottleneck problem and prolonging network life time for PMRC-based networks. They can also be applied for other multi-hop cluster-based sensor networks. The traffic-similar nodes distribution concept can be applied in optimizing sensor network deployment to achieve desired network life time

DECOR: Distributed construction of load balanced routing trees for many to one sensor networks

Many sensor networks suffer from the energy hole problem which is a special case of load imbalance caused by the funnelling effect of many sensor nodes transmitting their data to a single, central sink. In order to mitigate the problem, a balanced routing tree is often required and this can be constructed with either a centralised or distributed algorithm. Distributed solutions are typically less effective but are significantly cheaper than centralised solutions in terms of communication overhead and they scale better for the same reason. In this paper we propose a novel distributed algorithm for the construction of a load balanced routing tree. Our proposed solution, Degree Constrained Routing, is unique in that it aims to maximise global balance during construction rather that relying on rebalancing an arbitrary tree or only maximising local balance. The underlying principle is that if all nodes adopt the same number of children as each other while the routing tree grows, then the final tree will be globally balanced. Simulation results show that our algorithm can produce trees with improved balance which results in lifetimes increased by up to 80% compared to the next best distributed algorithm

A Hybrid Sink Repositioning Technique for Data Gathering in Wireless Sensor Networks

Wireless sensor network (WSN) is a wireless network that consists of spatially distributed autonomous devices using sensors to cooperatively investigate physical or environmental conditions. WSN has a hundreds or thousands of nodes that can communicate with each other and pass data from one node to another. Energy can be supplied to sensor nodes by batteries only and they are configured in a harsh environment in which the batteries cannot be charged or recharged simply. Sensor nodes can be randomly installed and they autonomously organize themselves into a communication network. The main constraint in wireless sensor networks is limited energy supply at the sensor nodes so it is important to deploy the sink at a position with respect to the specific area which is the area of interest; which would result in minimization of energy consumption. Sink repositioning is very important in modern day wireless sensor network since repositioning the sink at regular interval of time can balance the traffic load thereby decreasing the failure rate of the real time packets. More attention needs to be given on the Sink repositioning methods in order to increase the efficiency of the network. Existing work on sink repositioning techniques in wireless sensor networks consider only static and mobile sink. Not much importance is given to the hybrid sink deployment techniques. Multiple sink deployment and sink mobility can be considered to perform sink repositioning. Precise information of the area being monitored is needed to offer an ideal solution by the sink deployment method but this method is not a realistic often. To reallocate the sink, its odd pattern of energy must be considered. In this chapter a hybrid sink repositioning technique is developed for wireless sensor network where static and mobile sinks are used to gather the data from the sensor nodes. The nodes with low residual energy and high data generation rate are categorized as urgent and the nodes with high residual energy and low data generation rate are categorized as non-urgent. Static sink located within the center of the network collects the data from the urgent nodes. A relay is selected for each urgent sensor based on their residual energy. The urgent sensor sends their data to the static sink through these relay. Mobile sink collects the data from the non-urgent sensors. The performance of the proposed technique is compared with mobile base station placement scheme mainly based on the performance according to the metrics such as average end-to-end delay, drop, average packet delivery ratio and average energy consumption. Through the simulation results it is observed that the proposed hybrid sink repositioning technique reduces the energy hold problem and minimizes the buffer overflow problem thereby elongating the sensor network lifetime

Stochastic Models and Adaptive Algorithms for Energy Balance in Sensor Networks

We consider the important problem of energy balanced data propagation in wireless sensor networks and we extend and generalize previous works by allowing adaptive energy assignment. We consider the data gathering problem where data are generated by the sensors and must be routed toward a unique sink. Sensors route data by either sending the data directly to the sink or in a multi-hop fashion by delivering the data to a neighbouring sensor. Direct and neighbouring transmissions require different levels of energy consumption. Basically, the protocols balance the energy consumption among the sensors by computing the adequate ratios of direct and neighbouring transmissions. An abstract model of energy dissipation as a random walk is proposed, along with rigorous performance analysis techniques. Two efficient distributed algorithms are presented and analyzed, by both rigorous means and simulation. The first one is easy to implement and fast to execute. The protocol assumes that sensors know a-priori the rate of data they generate. The sink collects and processes all these information in order to compute the relevant value of the protocol parameter. This value is transmitted to the sensors which individually compute their optimal ratios of direct and neighbouring transmissions. The second protocol avoids the necessary a-priori knowledge of the data rate generated by sensors by inferring the relevant information from the observation of the data paths. Furthermore, this algorithm is based on stochastic estimation methods and is adaptive to environmental change

Active security mechanisms for wireless sensor networks and energy optimization for passive security routing

Wireless sensor networks consisting of numerous tiny low power autonomous sensor nodes provide us with the remarkable ability to remotely view and interact with the previously unobservable physical world. However, incorporating computation intensive security measures in sensor networks with limited resources is a challenging research issue. The objective of our thesis is to explore different security aspects of sensor networks and provide novel solutions for significant problems. We classify security mechanisms into two categories - active category and passive category. The problem of providing a secure communication infrastructure among randomly deployed sensor nodes requires active security measurements. Key pre-distribution is a well-known technique in this class. We propose a novel 2-Phase technique for key pre-distribution based on a combination of inherited and random key assignments from the given key pool to individual sensor nodes. We develop an analytical framework for measuring security-performance tradeoffs of different key distribution schemes. Using rigorous mathematical analysis and detailed simulation, we show that the proposed scheme outperforms the existing solution in every performance aspect. Secure data aggregation in wireless sensor networks is another challenging problem requiring active measures. We address the problem of stealthy attack where a compromised node sends wrong/fictitious data as a reply to a query. We propose a novel probabilistic accuracy model which enables an aggregator to compute accuracy of each sensor reading by exploiting spatial correlation among data values. We also propose some novel, energy efficient statistical methods to enable a user accept the correct value with a high probability. Increasing network lifetime is a passive security mechanism which enables many security mechanisms to work more efficiently. We define length-energy-constrained optimality criteria for energy-optimized routes that impose uniform energy distribution across the network, thus preventing expedited network partition. We propose three different distributed, nearly-stateless and energy efficient routing protocols that dynamically find optimal routes and balance energy consumption across the network. We show that global energy information acquired through this process utilized in conjunction with energy depletion control in the sensornet ensures a significant improvement in terms of network lifetime

Energy-efficient node selection algorithms with correlation optimization in wireless sensor networks

The sensing data of nodes is generally correlated in dense wireless sensor networks, and the active node selection problem aims at selecting a minimum number of nodes to provide required data services within error threshold so as to efficiently extend the network lifetime. In this paper, we firstly propose a new Cover Sets Balance (CSB) algorithm to choose a set of active nodes with the partially ordered tuple (data coverage range, residual energy). Then, we introduce a new Correlated Node Set Computing (CNSC) algorithm to find the correlated node set for a given node. Finally, we propose a High Residual Energy First (HREF) node selection algorithm to further reduce the number of active nodes. Extensive experiments demonstrate that HREF significantly reduces the number of active nodes, and CSB and HREF effectively increase the lifetime of wireless sensor networks compared with related works.This work is supported by the National Science Foundation of China under Grand nos. 61370210 and 61103175, Fujian Provincial Natural Science Foundation of China under Grant nos. 2011J01345, 2013J01232, and 2013J01229, and the Development Foundation of Educational Committee of Fujian Province under Grand no. 2012JA12027. It has also been partially supported by the "Ministerio de Ciencia e Innovacion," through the "Plan Nacional de I+D+i 2008-2011" in the "Subprograma de Proyectos de Investigacion Fundamental," Project TEC2011-27516, and by the Polytechnic University of Valencia, though the PAID-15-11 multidisciplinary Projects.Cheng, H.; Su, Z.; Zhang, D.; Lloret, J.; Yu, Z. (2014). Energy-efficient node selection algorithms with correlation optimization in wireless sensor networks. 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Real-Time Cross-Layer Routing Protocol for Ad Hoc Wireless Sensor Networks

Reliable and energy efficient routing is a critical issue in Wireless Sensor Networks (WSNs) deployments. Many approaches have been proposed for WSN routing, but sensor field implementations, compared to computer simulations and fully-controlled testbeds, tend to be lacking in the literature and not fully documented. Typically, WSNs provide the ability to gather information cheaply, accurately and reliably over both small and vast physical regions. Unlike other large data network forms, where the ultimate input/output interface is a human being, WSNs are about collecting data from unattended physical environments. Although WSNs are being studied on a global scale, the major current research is still focusing on simulations experiments. In particular for sensor networks, which have to deal with very stringent resource limitations and that are exposed to severe physical conditions, real experiments with real applications are essential. In addition, the effectiveness of simulation studies is severely limited in terms of the difficulty in modeling the complexities of the radio environment, power consumption on sensor devices, and the interactions between the physical, network and application layers. The routing problem in ad hoc WSNs is nontrivial issue because of sensor node failures due to restricted recourses. Thus, the routing protocols of WSNs encounter two conflicting issue: on the one hand, in order to optimise routes, frequent topology updates are required, while on the other hand, frequent topology updates result in imbalanced energy dissipation and higher message overhead. In the literature, such as in (Rahul et al., 2002), (Woo et al., 2003), (TinyOS, 2004), (Gnawali et al., 2009) and (Burri et al., 2007) several authors have presented routing algorithms for WSNs that consider purely one or two metrics at most in attempting to optimise routes while attempting to keep small message overhead and balanced energy dissipation. Recent studies on energy efficient routing in multihop WSNs have shown a great reliance on radio link quality in the path selection process. If sensor nodes along the routing path and closer to the base station advertise a high quality link to forwarding upstream packets, these sensor nodes will experience a faster depletion rate in their residual energy. This results in a topological routing hole or network partitioning as stated and resolved in and (Daabaj 2010). This chapter presents an empirical study on how to improve energy efficiency for reliable multihop communication by developing a real-time cross-layer lifetime-oriented routing protocol and integrating useful routing information from different layers to examine their joint benefit on the lifetime of individual sensor nodes and the entire sensor network. The proposed approach aims to balance the workload and energy usage among relay nodes to achieve balanced energy dissipation, thereby maximizing the functional network lifetime. The obtained experimental results are presented from prototype real-network experiments based on Crossbow’s sensor motes (Crossbow, 2010), i.e., Mica2 low-power wireless sensor platforms (Crossbow, 2010). The distributed real-time routing protocol which is proposed In this chapter aims to face the dynamics of the real world sensor networks and also to discover multiple paths between the base station and source sensor nodes. The proposed routing protocol is compared experimentally with a reliability-oriented collection-tree protocol, i.e., the TinyOS MintRoute protocol (Woo et al., 2003). The experimental results show that our proposed protocol has a higher node energy efficiency, lower control overhead, and fair average delay