Performance analysis of receive diversity in wireless sensor networks over GBSBE models

Wireless sensor networks have attracted a lot of attention recently. In this paper, we develop a channel model based on the elliptical model for multipath components involving randomly placed scatterers in the scattering region with sensors deployed on a field. We verify that in a sensor network, the use of receive diversity techniques improves the performance of the system. Extensive performance analysis of the system is carried out for both single and multiple antennas with the applied receive diversity techniques. Performance analyses based on variations in receiver height, maximum multipath delay and transmit power have been performed considering different numbers of antenna elements present in the receiver array, Our results show that increasing the number of antenna elements for a wireless sensor network does indeed improve the BER rates that can be obtained.

Virtual backbone routing structures in wireless ad-hoc networks

In this paper we studied several virtual routing structures (ring, ring-tree, cord, and mesh) which are scalable, independent on addresses, based on local information and partial global information for routing packets. These virtual routing structures are built on the top of the backbone nodes which are selected by considering power, connections, and immobility metrics.Our experimental results on the ns2 simulator and both TelosBand MicaZ sensor nodes tested platform prove that the virtual backbone structures are superior to the existing routing schemes and the different virtual structures fit in with the different physical scenarios.

Network resilience in low-resource mobile wireless sensor networks

Wireless sensor networks (WSNs) are deployed in numerous mission critical applications in which the network needs to remain active for as long as possible while delivering quality information to a base station. However, WSNs suffer from a wide range of attacks due to their limited processing and energy capabilities. Their resiliency, however, depends on fast recovery from such attacks being achieved. In recent work, the authors developed and implemented clustering, reprogramming and authentication protocols involved in recovering stationary WSNs with low resources. In this paper, we determine the additional resources required in implementing these protocols in a mobile WSN.

We present recovery protocols on TinyOS motes for a low-resourced, mobile deployment. We describe the issues we encountered in the implementation. We present times, RAM and ROM needed to run the recovery protocols and compare these with the stationary case, demonstrating that the additional cost of reprogramming in a mobile WSN is less than 25% of that in a stationary WSN and the additional cost of re-clustering in a mobile WSN is less than 9% of that in a stationary WSN. Authentication has an insignificant cost increase.

Secure connectivity model in wireless sensor networks (WSN) using first order Reed-Muller codes

In this paper, we suggest the idea of separately treating the connectivity and communication model of a Wireless Sensor Network (WSN). We then propose a novel connectivity model for a WSN using first order Reed-Muller Codes. While the model has a hierarchical structure, we have shown that it works equally well for a Distributed WSN. Though one can use any communication model, we prefer to use the communication model suggested by Ruj and Roy [1] for all computations and results in our work. Two suitable secure (symmetric) cryptosystems can then be applied for the two different models, connectivity and communication respectively. By doing so we have shown how resiliency and scalability are appreciably improved as compared to Ruj and Roy [1].

Channel estimation scheme for 3.9G wireless communication systems using RLS algorithm

Main challenges for a terminal implementation are efficient realization of the receiver, especially for channel estimation (CE) and equalization. In this paper, training based recursive least square (RLS) channel estimator technique is presented for a long term evolution (LTE) single carrier-frequency division multiple access (SC-FDMA) wireless communication system. This CE scheme uses adaptive RLS estimator which is able to update parameters of the estimator continuously, so that knowledge of channel and noise statistics are not required. Simulation results show that the RLS CE scheme with 500 Hz Doppler frequency has 3 dB better performances compared with 1.5 kHz Doppler frequency.

Flock inspired area coverage using wireless boid-like sensor agents

Simulated flocking is achievable using three boid rules [13]. We propose an area coverage model inspired by Reynolds’ flocking algorithm, investigating strategies for achieving quality coverage using flocking rules. Our agents are identical and autonomous, using only local sensory information for indirect communication. Upon deployment, agents are in the default separation mode. The cohesion rule would then guarantee that agents remain within the swarm, covering spaces with explored neighbour spaces. Four experiments are conducted to evaluate our model in terms of coverage quality achieved. We firstly investigate agents’ separation speed before the speed with which isolated agents re-organizes is investigated. The third experiment compares coverage quality achieved using our model with coverage quality achieved using random guessing. Finally, we investigate fault tolerance in the event of agents’ failures. Our model exhibits good separation and cohesion speed, achieving high quality coverage. Additionally, the model is fault tolerant and adaptive to agents’ failures.

Secure localization with attack detection in wireless sensor networks

Rapid technological advances have enabled the development of low-cost sensor networks for various monitoring tasks, where it is important to estimate the positions of a number of regular sensor nodes whose locations cannot be known apriori. We address the problem of localizing the regular nodes with range-based location references obtained from certain anchor nodes referred to as beacons, particularly in an adverse environment where some of the beacons may be compromised. We propose an innovative modular solution featuring two lightweight modules that are for dedicated functionalities, respectively, but can also be closely integrated. First, we harness simple geometric triangular rules and an efficient voting technique to enable the attack detection module, which identifies and filters out malicious location references. We then develop a secure localization module that computes and clusters certain reference points, and the position of the concerned regular node is estimated with the centroid of the most valuable reference points identified. Extensive simulations show that our attack detection module can detect compromised beacons effectively, and the secure localization module can subsequently provide a dependable localization service in terms of bounded estimation error. The integrated system turns out to be tolerant of malicious attacks even in highly challenging scenarios.

MAR : message-aware routing for opportunistic wireless ad hoc networks

In this paper we study the problem of routing in opportunistic wireless network, and propose a novel routing mechanism, message-aware routing (MAR). Using MAR, the messages can be prioritized at mobile nodes and the resources will be allocated accordingly. The MAR uses the message-aware socializing model to classify mobile nodes into different social groups. In MAR, nodes only maintain up-to-date routing information for the nodes in the same social group and the messages for the nodes in the same social group will have higher priority to be delivered. The MAR improves the routing efficiency in terms of reduced traffic and a higher delivery success rate. Further, MAR is constructed in decentralized way and does not require any centralized infrastructure. Experiments using NS2 simulator show that the MAR achieves higher delivery rate than the Epidemic and Prophet routing.

On the maximum throughput of two-hop wireless network coding

Network coding has shown the promise of significant throughput improvement. In this paper, we study the throughput of two-hop wireless network coding and explore how the maximum throughput can be achieved under a random medium access scheme. Unlike previous studies, we consider a more practical network where the structure of overhearing status between the intended receivers and the transmitters is arbitrary. We make a formal analysis on the network throughput using network coding upon the concept of network coding cliques (NCCs). The analysis shows that the maximum normalized throughput, subject to fairness requirement, is n/n+m, where n is the number of transmitters and m is the number of NCCs in a 2-hop wireless network. We have also found that this maximum throughput can be achieved under a random medium access scheme when the medium access priority of the relay node is equal to the number of NCCs in the network. Our theoretical findings have been validated by simulation as well.

Implementing recovery in low-resource stationary wireless sensor networks

Implementation of certain types of protocols on wireless sensor networks (WSNs) can be difficult due to the architecture of the motes. Identification of these issues and recommendations for workarounds can be very useful for the WSN research community testing hardware. In recent work, the authors developed and implemented clustering, reprogramming and authentication protocols involved in recovering WSNs with low resources. In attempting to integrate these protocols, several issues arose in the implementation phase connected to pre-set configurations of the motes used. In this paper, we describe the issues arising in integrating our protocols using Zigbee with IEEE 802.15.4 and the reprogramming module Deluge, and compare our challenges and solutions with those faced by other researchers in this area. Finally, we provide recommendations for consideration by researchers who may in future consider integrating several protocols on these platforms.