Current Issue : October - December Volume : 2018 Issue Number : 4 Articles : 5 Articles
With the increasing concern over marine applications in recent years, the technology of underwater wireless sensor networks\nhas received considerable attention. In underwater wireless sensor networks, the gathered data are sent to terrestrial\ncontrol center through multi-hops for further processing. Underwater wireless sensor networks usually consist\nof three types of nodes: ordinary nodes, anchor nodes, and sink nodes. The data messages are transferred from an ordinary\nnode or an anchored node to one of the sink nodes by discrete hops. Data forwarding algorithms are at the core\nposition of underwater wireless sensor networks, which determines data in what way to forward. However, the existing\ndata forwarding algorithms all have problems that transmission delay is too high and delivery ratio is low. Thus, we propose\na data forwarding algorithm based on estimated Hungarian method to improve delivery ratio and reduce transmission\ndelay. The estimated Hungarian method is applied to solve the assignment problem in data forwarding process,\nwhere the anchor nodes receive the forwarding requests from ordinary nodes and optimize the waiting queue. By applying\nthis method in underwater wireless sensor networks, data forwarding has great advantages in success rate and transmission\ndelay, which has been validated by both analysis and simulation results....
Localizing a jammer in an indoor environment in wireless sensor networks\nbecomes a significant research problem due to the ease of blocking the communication\nbetween legitimate nodes. An adversary may emit radio frequency\nto prevent the transmission between nodes. In this paper, we propose detecting\nthe position of the jammer indoor by using the received signal strength\nand Kalman filter (KF) to reduce the noise due to the multipath signal caused\nby obstacles in the indoor environment. We compare our work to the Linear\nPrediction Algorithm (LP) and Centroid Localization Algorithm (CL). We\nobserved that the Kalman filter has better results when estimating the distance\ncompared to other algorithms....
This study aims to solve time-space uncertainties due to the narrow network channel bandwidth and long\ntransmission delay of an underwater acoustic sensor network when a node is using a channel. This study proposes\na MAC protocol (BSPMDP-MAC) for an underwater acoustic sensor network based on the belief state space. This\nprotocol can averagely divide the time axis of a sensor�s receiving nodes into n slots. The action state information\nof a sensor�s transmission node was divided by the grades of link quality and the residual energy of each node. The\nreceiving nodes would obtain the decision strategy sequence of the usage rights of the competitive channels of\nthe sensor�s transmission nodes according to the joint probability distributions of historical observations and action\ninformation of channel occupancy. The transmission nodes will transmit data packets to the receiving nodes in\nturns in allocated slots, according to the decision strategy sequence, and the receiving nodes will predict the\nchannel occupancy and perceive the belief states and access actions in the next cycle, according to the present\nbelief states and actions. These experimental simulation results show that this protocol can reduce the collision rate\nof data packets, improve the network throughput and transmission success rate of data packets, and reduce the\nenergy overhead of the network....
This article studies the performance of a wireless sensor network with cognitive radio capabilities to gather information\nabout structural health monitoring of buildings in case of seismic activity. Since the use of the local area network is intensive\nin office and home environments, we propose the use of empty cellular channels (primary system). As such, the\nstructural health monitoring does not degrade the local communications. Thus, the wireless sensor network for structural\nhealth monitoring acts as secondary network. Two discrete-time analytical approaches are proposed and developed\nto evaluate the system performance in terms of both the average packet delay and average energy consumption. The first\none is an approximation suitable for the case when the time slot duration is small relative to the mean call inter-arrival\ntime. The second model is accurate for any time slot duration and inter-arrival times...
Lightweight block ciphers play an indispensable role for the security in the context of pervasive computing. However,\nthe performance of resource-constrained devices can be affected dynamically by the selection of suitable cryptalgorithms,\nespecially for the devices in the resource-constrained devices and/or wireless networks. Thus, in this paper, we study\nthe trade-off between security and performance of several recent top performing lightweight block ciphers for the\ndemand of resource-constrained Industrial Wireless Sensor Networks. Then, the software performance evaluation\nabout these ciphers has been carried out in terms of memory occupation, cycles per byte, throughput, and a relative\ngood comprehensive metric. Moreover, the results of avalanche effect, which shows the possibility to resist possible\ntypes of different attacks, are presented subsequently. Our results show that SPECK is the software-oriented lightweight\ncipher which achieves the best performance in various aspects, and it enjoys a healthy security margin at the same\ntime. Furthermore, PRESENT, which is usually used as a benchmark for newer hardware-oriented lightweight ciphers,\nshows that the software performance combined with avalanche effect is inadequate when it is implemented. In the\nreal application, there is a need to better understand the resources of dedicated platforms and security requirement,\nas well as the emphasis and focus. Therefore, this case study can serve as a good reference for the better selection of\ntrade-off between performance and security in constrained environments....
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