GSHMAC: Green and Secure Hybrid Medium Access Control for Wireless Sensor Network

The cost efficiency of wireless platforms and their easy deployment enable the applicability of it in widespread application domains. Wireless sensor networks (WSNs) are not excluded from it. Their application domains vary from industrial monitoring to military applications. A WSN is a resource-constrained network and energy of the WSN node is a valuable resource. Like every other network, WSNs are also vulnerable to security attacks. A security attack can results in networks consuming more resources, leading to earlier depletion of node energy. A significant part of the resource consumption in a WSN is controlled by the medium access control (MAC) mechanism. This paper focuses on WSN MAC mechanisms and countermeasures for attacks targeting the MAC layer in a WSN. Denial of sleep attacks are the most relevant for WSN MAC as these types of attacks have shattered effects, which bring down the sensor lifetime from years to days. This paper proposes a secure hybrid MAC mechanism, Green and Secure Hybrid Medium Access Control (GSHMAC) to overcome the devastating effect of WSN MAC attacks. The proposed mechanism provides features such as collision threshold-based MAC mode control and countermeasures on WSN MAC using internal MAC mechanisms. GSHMAC shows improved energy-efficiency, delay, and throughput in the presence of attacks, as compared with state-of-art secure MAC mechanisms.     

Collaborative beamforming for wireless sensor networks with Gaussian distributed sensor nodes

Collaborative beamforming has been recently introduced in the context of wireless sensor networks (WSNs) to increase the transmission range of individual sensor nodes. The challenge in using collaborative beamforming in WSNs is the uncertainty regarding the sensor node locations. However, the actual sensor node spatial distribution can be modeled by a properly selected probability density function (pdf). In this paper, we model the spatial distribution of sensor nodes in a cluster of WSN using Gaussian pdf. Gaussian pdf is more suitable in many WSN applications than, for example, uniform pdf which is commonly used for flat ad hoc networks. The average beampattern and its characteristics, the distribution of the beampattern level in the sidelobe region, and the distribution of the maximum sidelobe peak are derived using the theory of random arrays. We show that both the uniform and Gaussian sensor node deployments behave qualitatively in a similar way with respect to the beamwidths and sidelobe levels, while the Gaussian deployment gives wider mainlobe and has lower chance of large sidelobes.     

Application modeling for performance evaluation on event-triggered wireless sensor networks

This paper presents an approach for event-triggered wireless sensor network (WSN) application modeling, aiming to evaluate the performance of WSN configurations with regards to metrics that are meaningful to specific application domains and respective end-users. It combines application, environment-generated workload and computing/communication infrastructure within a high-level modeling simulation framework, and includes modeling primitives to represent different kind of events based on different probabilities distributions. Such primitives help end-users to characterize their application workload to capture realistic scenarios. This characterization allows the performance evaluation of specific WSN configurations, including dynamic management techniques as load balancing. Extensive experimental work shows that the proposed approach is effective in verifying whether a given WSN configuration can fulfill non-functional application requirements, such as identifying the application behavior that can lead a WSN to a break point after which it cannot further maintain these requirements. Furthermore, through these experiments, we discuss the impact of different distribution probabilities to model temporal and spatial aspects of the workload on WSNs performance, considering the adoption of dynamic and decentralized load balancing approaches.     

Cross-Layer Collaborative In-Network Processing in Multihop Wireless Sensor Networks

Emerging wireless sensor network (WSN) applications demand considerable computation capacity for in-network processing. To achieve the required processing capacity, cross-layer collaborative in-network processing among sensors emerges as a promising solution: sensors do not only process information at the application layer, but also synchronize their communication activities to exchange partially processed data for parallel processing. However, scheduling computation and communication events is a challenging problem in WSNs due to limited resource availability and shared communication medium. In this work, an application-independent task mapping and scheduling solution in multihop homogeneous WSNs, multihop task mapping and scheduling (MTMS), is presented that provides real-time guarantees. Using our proposed application model, the multihop channel model, and the communication scheduling algorithm, computation tasks and associated communication events are scheduled simultaneously. The dynamic voltage scaling (DVS) algorithm is presented to further optimize energy consumption. Simulation results show significant performance improvements compared with existing mechanisms in terms of minimizing energy consumption subject to delay constraints     

Application Oriented Multi Criteria Optimization in WSNs Using on AHP

With the increasing number and variety of Wireless Sensor Network (WSN) applications the need to define a suitable protocol design model that fits their specific requirements and operation has become even more pressing. The traditional methods and the well known OSI layered model prove to be inadequate for WSNs. Utilizing cross layer interactions on the other hand leads to increased efficiency in operation and prolonging the network lifetime. Similarly, proper optimization can even further add to improving the performance and reducing energy consumption in WSN. However there is no common ground to compare the suggested solutions or there is no well defined methodology for determining the optimization parameters for each specific case. In this paper we discuss two major issues: the first one is definition of optimization parameters for WSN and check for their consistency, the second one is how the suggested approach can be incorporated in a cross layer framework to provide adaptivity to different application requirements while maximizing the network performance and prolonging the network lifetime.     

基于遗传聚类的无线传感器负载均衡路由算法

通常的无线传感器分簇网络存在节点负载不均衡的问题。为均衡各节点能量消耗,延长网络生存周期,将K均值算法与遗传算法相结合,提出一种负载均衡的无线传感器网络路由算法,算法利用遗传算法的全局寻优能力以克服传统K均值算法的局部性和对初始中心的敏感性,实现了传感器网络节点自适应成簇与各节点负载均衡。仿真实验表明,该算法显著延长了网络寿命,相对于其他分簇路由算法,其网络生存时间延长了约43%。     

A novel chain-based clustering for green communication in wireless sensor network

The rapid growth of the Internet of Things (IoT) creates a high requirement for data collected through wireless sensor networks (WSNs), resulting in a lot of emphasis on WSN data collecting in recent decades. However, the resource-constrained nature of sensor devices exerts heavy constraints for acquiring the optimal network performance. To resolve this concern, this paper proposes the Chain-based Energy-Efficient Clustering (CBEEC) Routing Protocol that considers nodes of two heterogeneous levels of energy (normal level and advanced level). The number of advanced nodes in CBEEC is analytically determined and hence are analytically allocated. However, normal nodes are stochastically deployed in the vicinity of advanced nodes. The data transmission is performed among the advanced nodes in the form of chain and from there it is forwarded to base station (BS). Consequently, it preserves immense amount of energy for the network. The performance of CBEEC is empirically investigated with benchmarks of different performance metrics and simulation outcomes showing that the CBEEC outperforms state-of-the-art routing protocols.     

基于角色的无线传感网络中间件研究

根据无线传感网络中节点扮演角色的多样性及角色职责的差异,提出无线传感网络角色映射框架模型。在此角色映射框架基础上,设计并实现基于角色的无线传感网络中间件RobMSN。从语义和规约的形式化角度定义了角色映射的规则约束,系统地解决了角色映射抽象的语义冲突问题,使得角色映射的上下文充分地体现在中间件的角色规约中。利用RobMSN把应用程序映射为节点在网络中具体所承担的角色,解决了无线传感网络中间件的跨平台要求和应用服务的动态性问题。最后,以一个应用开发实例来说明RobMSN中间件的设计和开发流程。     

Energy awareness workflow model for wireless sensor nodes

Before the development of a large‐scale wireless sensor network (WSN) infrastructure, it is necessary to create a model to evaluate the lifespan of the infrastructure, the system performance and the cost so that the best design solution can be obtained. Energy consumption is an important factor that influences the lifespan of WSNs. One of the ways to extend the lifespan of WSNs is to design wireless sensor nodes with low power consumption. This involves component selection and the optimisation of hardware architecture, monitoring software system and protocols to satisfy the requirements of the particular applications. This paper proposes a comprehensive model to describe the workflow of a wireless sensor node. Parameter setup and energy consumption calculation are demonstrated through the model simulation. It provides a mathematical approach to dynamically evaluate the energy consumption of a sensor node. This will benefit the development of wireless sensor nodes based on microprocessors with limited computational capability. Therefore, the model can be applied in dynamic power management systems for wireless sensor nodes or in wireless communication protocols with energy awareness, in particular, for WSNs with self‐organisation. More importantly, the generalisation of the model may be employed as a standard paradigm for the development of wireless sensor node with energy awareness. Copyright © 2012 John Wiley & Sons, Ltd.     

Wireless Sensor Networks in IPv4/IPv6 Transition Scenarios

The wireless sensor networks (WSNs) concept was appeared in the middle of 90s and have been a subject under intensive research in the past few years. Several factors have contributed to this, but the potential for application of WSNs in almost every aspect of day-to-day life is the predominant one. This type of networks has been developed using proprietary solutions instead of standard solutions. More recently, the importance of standards motivated the use of IETF standards in WSNs, making the Internet integration easier. However, more efforts are necessary in order to provide a full integration. The WSNs use mainly IPv6 protocol, but the IPv4 is the predominant one in the Internet. As a consequence, IPv4 to IPv6 transition mechanisms must be provided to allow the interaction between all Internet connected devices independently of the supported IP version. It is also critical to provide a standard application interface to make easier the application development and independently of the hardware platform used. The RESTfull Web services can provide this standard interface. So, combine RESTfull Web services with IPv4 to IPv6 transition mechanisms can increase the WSN services dissemination. The transition mechanisms and the REST Web services are supported in the gateway in order to save the wireless sensor device resources’. The smartphone with Internet connectivity can also be the drive to the WSNs growth, because user-friendly applications can be used to retrieve and collect sensed data. This paper proposes a solution based on REST web services to permit the interaction between a mobile application and the IPv6 compliant WSN.     

e‐LiteSense: Self‐adaptive energy‐aware data sensing in WSN environments

Currently deployed in a wide variety of applicational scenarios, wireless sensor networks (WSNs) are typically a resource‐constrained infrastructure. Consequently, characteristics such as WSN adaptability, low‐overhead, and low‐energy consumption are particularly relevant in dynamic and autonomous sensing environments where the measuring requirements change and human intervention is not viable. To tackle this issue, this article proposes e‐LiteSense as an adaptive, energy‐aware sensing solution for WSNs, capable of auto‐regulate how data are sensed, adjusting it to each applicational scenario. The proposed adaptive scheme is able to maintain the sensing accuracy of the physical phenomena, while reducing the overall process overhead. In this way, the adaptive algorithm relies on low‐complexity rules to establish the sensing frequency weighting the recent drifts of the physical parameter and the levels of remaining energy in the sensor. Using datasets from WSN operational scenarios, we prove e‐LiteSense effectiveness in self‐regulating data sensing accurately through a low‐overhead process where the WSN energy levels are preserved. This constitutes a step‐forward for implementing self‐adaptive energy‐aware data sensing in dynamic WSN environments.     

Optimal base-station locations in two-tiered wireless sensor networks

We consider generic two-tiered wireless sensor networks (WSNs) consisting of sensor clusters deployed around strategic locations, and base-stations (BSs) whose locations are relatively flexible. Within a sensor cluster, there are many small sensor nodes (SNs) that capture, encode, and transmit relevant information from a designated area, and there is at least one application node (AN) that receives raw data from these SNs, creates a comprehensive local-view, and forwards the composite bit-stream toward a BS. This paper focuses on the topology control process for ANs and BSs, which constitute the upper tier of two-tiered WSNs. Since heterogeneous ANs are battery-powered and energy-constrained, their node lifetime directly affects the network lifetime of WSNs. By proposing algorithmic approaches to locate BSs optimally, we can maximize the topological network lifetime of WSNs deterministically, even when the initial energy provisioning for ANs is no longer always proportional to their average bit-stream rate. The obtained optimal BS locations are under different lifetime definitions according to the mission criticality of WSNs. By studying intrinsic properties of WSNs, we establish the upper and lower bounds of maximal topological lifetime, which enable a quick assessment of energy provisioning feasibility and topology control necessity. Numerical results are given to demonstrate the efficacy and optimality of the proposed topology control approaches designed for maximizing network lifetime of WSNs.     

Accuracy,latency, and energy cross‐optimization in wireless sensor networks through infection spreading

In this paper, cross‐optimization of accuracy, latency, and energy in wireless sensor networks (WSNs) through infection spreading is investigated. Our solution is based on a dual‐layer architecture for efficient data harvesting in a WSN, in which, the lower layer sensors are equipped with a novel adaptive data propagation method inspired by infection spreading and the upper layer consists of randomly roaming data harvesting agents. The proposed infection spreading mechanisms, namely random infection (RI) and linear infection (LI), are implemented at the lower layer. The entire sensor field is dynamically separated into several busy areas (BA) and quiet areas (QA). According to the BA or QA classification, the level of importance is defined, on which, the optimal number of infections for a particular observation is evaluated. Therefore, the accessed probability for observations with a relatively higher importance level is adaptively increased. The proposed mechanisms add further value to the data harvesting operation by compensating for its potential lack of coverage due to random mobility and tolerable delay, thus a relatively higher accuracy and latency requirements can be guaranteed for the optimization of energy consumption in a dynamically changing environment. Further, with the cost of processing simple location information, LI is proved to outperform RI. Copyright © 2010 John Wiley & Sons, Ltd.     

Connectivity Analysis for Wireless Sensor Networks with Antenna Array Integrated Central Node

In a wireless sensor network (WSN), after gathering information, tiny sensor nodes need to transmit data to a sink. It is important to guarantee that each node can communicate with a sink. Due to the multi-hop communication of WSNs, an essential condition for reliable transmission is completely connectivity of a network. Adaptive or smart antenna (SA) techniques in WSNs have been a topic of active research in recent years. These techniques have been shown to be effective with respect to decreasing energy consuming via specified regions which are formed by the SA beams. In this paper, we propose a probabilistic technique to determine the network connectivity probability of the SA integrated WSN. We employ the geometric shape model to evaluate the network connectivity probability of the WSN using the SA beam specifications. The sensor node density to satisfy the desired network connectivity is determined in terms of the beam-width of the antenna array and node transmission range. The analytical results agree with the simulation results by less than 4.7 % error in the average.     

基于遗传聚类的无线传感器负载均衡路由算法

通常的无线传感器分簇网络存在节点负载不均衡的问题。为均衡各节点能量消耗,延长网络生存周期,将K均值算法与遗传算法相结合,提出一种负载均衡的无线传感器网络路由算法,算法利用遗传算法的全局寻优能力以克服传统K均值算法的局部性和对初始中心的敏感性,实现了传感器网络节点自适应成簇与各节点负载均衡。仿真实验表明,该算法显著延长了网络寿命,相对于其他分簇路由算法,其网络生存时间延长了约43%。     

Low-cost group rekeying for unattended wireless sensor networks

Wireless sensor networks (WSNs) are made up of large groups of nodes that perform distributed monitoring services. Since sensor measurements are often sensitive data acquired in hostile environments, securing WSN becomes mandatory. However, WSNs consists of low-end devices and frequently preclude the presence of a centralized security manager. Therefore, achieving security is even more challenging. State-of-the-art proposals rely on: (1) attended and centralized security systems; or (2) establishing initial keys without taking into account how to efficiently manage rekeying. In this paper we present a scalable group key management proposal for unattended WSNs that is designed to reduce the rekeying cost when the group membership changes.     

Unequal Clustering Protocols for Wireless Sensor Networks—Taxonomy,Comparison and Simulation

Wireless Sensor Network (WSN) consists of randomly distributed sensor nodes which can collect, process, route and transmit data from their respective environment. Most of the research on WSN is oriented towards optimizing utilization of finite resources of Sensor Nodes to increase the overall network operative time. Recent literature on WSNs reveals that hierarchical routing unequal clustering methodologies are gaining popularity due to energy efficiency, load balancing and scalability. In literature, numerous surveys on clustering methodologies are available which address different equal clustering methods. The unequal clustering protocols, which have their own attributes viz. balance load distribution, hot spot mitigation and energy efficiency, are comparatively less explored. This motivated us to undertake the present study on the taxonomy, comparison and simulation analysis of different methodologies pertaining to less explored unequal clustering protocols. Our base metrics for comparison of different unequal clustering protocols are scalability, energy efficiency & load balancing capability of the resulting network. A comprehensive discussion has also been presented to highlight the various advantages and disadvantages of different unequal clustering protocols. Further, we have summarized the study of unequal clustering protocols in the tabular form.

     

Evaluating routing metric composition approaches for QoS differentiation in low power and lossy networks

The use of Wireless Sensor Networks (WSN) in a wide variety of application domains has been intensively pursued lately while Future Internet designers consider WSN as a network architecture paradigm that provides abundant real-life real-time information which can be exploited to enhance the user experience. The wealth of applications running on WSNs imposes different Quality of Service requirements on the underlying network with respect to delay, reliability and loss. At the same time, WSNs present intricacies such as limited energy, node and network resources. To meet the application’s requirements while respecting the characteristics and limitations of the WSN, appropriate routing metrics have to be adopted by the routing protocol. These metrics can be primary (e.g. expected transmission count) to capture a specific effect (e.g. link reliability) and achieve a specific goal (e.g. low number of retransmissions to economize resources) or composite (e.g. combining latency with remaining energy) to satisfy different applications needs and WSNs requirements (e.g. low latency and energy consumption at the same time). In this paper, (a) we specify primary routing metrics and ways to combine them into composite routing metrics, (b) we prove (based on the routing algebra formalism) that these metrics can be utilized in such a way that the routing protocol converges to optimal paths in a loop-free manner and (c) we apply the proposed approach to the RPL protocol specified by the ROLL group of IETF for such low power and lossy link networks to quantify the achieved performance through extensive computer simulations.     

On the energy utilization for WSN based on BPSK over the Generalized-K shadowed fading channel

Energy is a scarce resource in the battery-powered nodes of wireless sensor networks (WSNs). In this paper the energy utilization for WSN based on BPSK communications has been investigated over the Generalized-K shadowed fading channel. A comprehensive analysis is reported based on the various important performance metrics like: amount of fading, average bit error probability, outage probability and energy utilized per bit (EUB). Simulation results reveal that composite use of shadowing and fading degrade energy levels to a considerable extent and hence contribute in downsizing the network life-span. We have derived the EUB metric and performed its evaluation with respect to optimal transmit energy levels by varying fading and shadowing severity parameters. We also considered the impact of varying transmit energy levels on the outage probability and hence on transmit and EUB levels. Although, embedding of training sequences and re-transmissions do help in enhancing effective synchronization and improved reliability, but this is done at a cost of higher energy utilization. Under the given set of assumptions, it is observed that an decrease in fading by about 11 %, improves the EUB by about 7 %. With increase in outage probability by about 10 %, EUB improves by about 3 %. An increase in SNR by 6 % improves the EUB levels by about 7 %. The investigations reported in this paper may enable designers to optionally choose suitable parameters to make WSN communications energy-efficient.     

Clustering Based Two Dimensional Motion of Sink Node in Wireless Sensor Networks

The wireless sensor network (WSN) is always known for its limited-energy issues and finding a good solution for energy minimization in WSNs is still a concern for researchers. Implementing mobility to the sink node is used widely for energy conservation or minimization in WSNs which reduces the distance between sink and communicating nodes. In this paper, with the intention to conserve energy from the sensor nodes, we designed a clustering based routing protocol implementing a mobile sink called ‘two dimensional motion of sink node (TDMS)’. In TDMS, each normal sensor node collects data and send it to their respective leader node called cluster head (CH). The sink moves in the two dimensional direction to collect final data from all CH nodes, particularly it moves in the direction to that CH which has the minimum remaining energy. The proposed protocol is validated through rigorous simulation using MATLAB and comparisons have been made with WSN’s existing static sink and mobile sink routing protocols over two different geographical square dimensions of the network. Here, we found that TDMS model gives the optimal result on energy dissipation per round and increased network lifetime.