Abstract:

Abstract:Power control scheme is used to reduce energy consumption,but asymmetric transmit powers is the problem which can result in increased collisions and degraded throughput in the scheme. A system model following pareto distribution according to a real network situation is proposed. The performance of the power control scheme in saving energy for wireless sensor networks is studied in this paper. A power control scheme based on SMAC(sensor-MAC) for wireless sensor networks is proposed and evaluated. In the new scheme,the optimum neighbor nodes are selected by a scheduling algorithm which can improve the network topology,reduce the collisions,increase goodput,and confirm the network connectivity. The message is transmitted with the optimum power. Furthermore,the protocol provides a fair share of the medium to low power and high power nodes by the reactive mechanism. The experimental results demonstrate that the new power control MAC(media access control) protocol provides longer lifetime and higher goodput than the current important protocols.

Abstract:In this paper,a hierarchical clustering protocol for long-lived sensor network is proposed. EADEEG(an energy-aware data gathering protocol for wireless sensor networks) achieves a good performance in terms of lifetime by minimizing energy consumption for communications and balancing the energy load among all nodes. EADEEG adopts a new clustering parameter for cluster head election,which can better handle the hetergenous energy capacities. Furthermore,it also adopts a simple but efficient approach,namely intra-cluster coverage to cope with the fractional area coverage problem. Through turning off redundant nodes,while the remaining nodes stay active to provide continuous service,the network lifetime can be significantly prolonged. Experimental results have shown that EADEEG can satisfy the desired coverage fraction and outperform LEACH(low energy adaptive clustering hierarchy) ,PEGASIS(power-efficient gathering in sensor information systems) and DEEG(distributed energy-efficient data gathering and aggregation protocol) in terms of network lifetime.

Abstract:Wireless sensor networks are characterized by centralized data gathering, multi-hop communication and many-to-one traffic pattern. These three characteristics may give rise to funneling effects that can lead to severe packet collision, network congestion, packet loss and even congestion collapse. This can also result in hotspots of energy consumption that may cause premature death of sensor nodes and even premature death of entire network. Load-Balancing techniques can effectively avoid the occurrence of funneling effects. Based on the static data gathering wireless sensor networks and motivated by the idea of supply and demand network, a distributed algorithm is proposed in this paper to organize the sensor node into a balanced deal network that can balance the load of nodes. The network structure constructed by this approach is not a load-balancing tree, but a load-balancing network. Experimental results validate the effectiveness of this approach.

Abstract:Wireless multimedia sensor networks(WMSNs) transfer information-intensive data(e.g. audio,video,image) ,so it is necessary to utilize wireless channel efficiently. Header compression is a useful mechanism which can reduce the amount of data transferred and can improve channel utilization efficiency. Based on the characteristics of WMSNs,an advanced adaptive header compression(AAHC) scheme is proposed,which adjusts the parameters of compression algorithm according to the exact estimation of wireless channel state and adopts UDP(user datagram protocol) Lite as its transport layer protocol. This scheme can get high compression ratio and error-resistant robustness at the same time. The simulation results show that AAHC scheme outperforms the traditional ROHC(robust header compression) scheme and CRTP(compressed RTP) scheme.

Abstract:Decision fusion rules under fading channel in wireless sensor networks are investigated in this paper. Local decisions made by local sensor nodes may be lost or corrupted while transmitted to the fusion center via a fading channel. A series of fusion rules are proposed under the assumption of Rayleigh channel model. Likelihood ratio rule has been shown optimal through theoretical analysis and simulation. However, it consumes system resource and requires good knowledge of local and channel information, which is not easily available in resource-constrained sensor networks. Three sub-optimal alternatives are proposed, which have less computation and information cost. They perform well in their respective SNR (signal-to-noise ratio) range. Finally, it is found that in resource-constrained wireless sensor networks, a tradeoff should be considered among performance, resource cost and computation complexity while choosing the fusion rules.

Abstract:Data sinking is one of the typical transmission patterns in WSN (wireless sensor network). There is inherent unbalanced traffic load distribution in such funnel like transmission. A case in hop-based sinking (HBS) model is found more intricate than simple thought that inner nodes burden more forwarding tasks, showing the inverse direction within the same hop level comparing with global trend. With global trend. With a simple weighted average mechanism, a continuous gradient parameter is introduced, which will be dedicated to instructing how to forward data to sink in place of hop count, namely fine-grain gradient sinking (FGS). Through traffic analysis and detailed simulation, in FGS model network turns out to be smoother on traffic load distribution and more efficient on data forwarding than that HBS model.

Abstract:Motivated by the directional sensing feature of video sensor, a direction adjustable sensing model is proposed first in this paper. Then, the coverage-enhancing problem in directional sensor networks is analyzed and defined. Moreover, a potential field based coverage-enhancing algorithm (PFCEA) is presented. By introducing the concept of “centroid”, the pending problem is translated into the centroid points’ uniform distribution problem. Centroid points repel each other to eliminate the sensing overlapping regions and coverage holes, thus enhance the whole coverage performance of the directional sensor network. A set of simulation results are performed to demonstrate the effectiveness of the proposed algorithm.

Abstract:In order to design a low-calculation and high-precision TOA (time of arrival) estimation algorithm for UWB (ultra wideband) based wireless sensor network (WSN), a two-step TOA estimation method which jointly employs energy-detection (ED) and match-filtering (MF) is proposed in this paper. Based on analyzing the principles of the two-step method, it is pointed out that the success rate of DP (direct path) block detection in the first step and the setting of MF-threshold-factor in the second step are the key issues that affect the performance of the method. Algorithm selection of the first step and setting of the energy integration interval, which are the two factors that affect the success rate of DP block detection, are discussed through simulations. The idea of DMR (DP to minimum energy sample ratio) based MF-threshold-factor selection is proposed, and the mathematical model of the relationship between DMRs and the optimal MF-threshold-factors are built. Results show that the proposed two-step method greatly outperforms the one-step energy-detection based non-coherent method, while largely decreases the computational complexity compared to the one-step match-filtering based coherent method, so that the two-step method is more appropriate for application to sensor nodes which need to be designed with low complexity and low power consumption.

Abstract:The traditional data centric storage method has a serious problem named hotspot problem, which appears near the sink and home node. Hotspot problem causes the nodes near the hotspot consume much more energy than other nodes, which seriously shortens the lifetime of the sensor networks. In this paper, a method distributing multiple sink nodes around the sensor networks is proposed to solve the hotspot problem around the sink. A load balance data storage method based on ring and a query processing algorithm for such a kind of data storage method are proposed to solve the hotspot problem around the home node. First, the ring based load balance data storage method divides the sensor networks into a lot of rings and stores data among all nodes within a ring. Second, different rings alternatively work during the working time of the network, which avoids the hotspot problem further. Finally, the query processing algorithm based on the load balance data storage method makes all nodes within a ring cooperatively answer the user’s query. Although the ring based load balance data storage method and the query processing algorithm consume more energy than the traditional method when answering a user’s query, the method makes all nodes within the network consume energy evenly, which avoids the hotspot problem of the traditional method, so the lifetime of sensor networks can be extended. Experimental results also show that the ring based load balance data storage method and the query processing algorithm can solve the hotspot problem and prolong the lifetime of the sensor networks.

Abstract:This paper presents a filter-based algorithm called PREDICTOR for optimizing multidimensional K-NN queries in WSN. A filter installed at each sensor node is a node value distribution range. It is used to prevent the node from sending the data that belongs to the covering range of the filter, and so the node's energy is saved. The server keeps the historical sample data of all the nodes, and determines filters for them according to the query requirement and the samples. Three optimization strategies are proposed: (1) the method for dynamically adjusting the assignment strategies of the filter covering ranges so that a node with little chance to contribute to the final result is assigned with a larger covering range; (2) the method for sharing the filter among nodes so that the nodes with similar historical data are assigned with the same filter; (3) the method for transmitting filters in a compressed way to reduce the cost of filter updating for different K-NN queries. Evaluation experiment results prove the efficiency of the algorithm PREDICTOR in energy saving. Compared with the naive method, this approach can reduce the transmission volume dramatically.

Abstract:Task allocation is a typical problem in the area of high performance computing and has been extensively studied in the past. However, existing algorithms cannot be directly used in WSN (wireless sensor network) due to severe energy constraint. A nested optimization technique based on genetic algorithm is proposed for energy-efficient task allocation in multi-hop clusters. The general optimization object can meet application’s real-time requirement while realizing energy efficiency. Optimal solution can be achieved by incorporating GA-based task mapping, GA-based routing, communication scheduling and dynamic voltage scaling (DVS). Performance is evaluated through simulations with randomly generated task graphs and simulation results show better solution in terms of real-time and energy-efficiency compared with random optimization techniques.

Abstract:The existence of faulty sensor measurements in wireless sensor networks (WSNs) will cause not only a degradation of the network quality of service but also a huge burden of the limited energy. This paper investigates using the spatial correlation of sensor measurements to detect the faults in WSNs. Specially, (1) a novel approach of weighting the neighbors' measurements is presented, (2) a method to characterize the difference between sensor measurements is introduced, (3) a weighted median fault detection scheme (WMFDS) is proposed and evaluated for both binary decisions and real number measurements. Theoretical analysis and simulation results show that the proposed WMFDS can attractively obtain the high detection accuracy and considerably reduce the false alarm probability even in the existence of large fault sets. It is demonstrated that the proposed WMFDS is of excellent performance in fault detection for WSNs.

Abstract:The design of key management schemes and protocols, whose main objective is to provide secure and reliable communication, is one of the most important aspects and basic research field of secure wireless sensor networks. The key management in wireless sensor networks meets many new challenges due to its intrinsic properties. In this paper, the secure and performance evaluation criterion of key management is introduced, the taxonomy for the key management schemes and protocols is proposed, the classic key management schemes and protocols are discussed and compared in detailed, and finally the open research problems and the possible solution are also pointed out. Recent related work indicates that future work will focus on some key issues such as fully distributed, self-organized, fault-tolerance and intrusion-tolerance, and location-aware etc.

Abstract:This paper proposes a reliable pairwise key-updating (RPKU) scheme for clustered WSNs via predistribution and local collaboration approaches. Based on the modified version of Blom's matrix construction, this scheme can extend and shrink the pairwise keys in WSNs with the network topology changes. This scheme also presents a hierarchical key distribution method in the clustered WSNs, guaranteeing that any pair of neighboring nodes can find a common secret key between themselves. Comparison and simulation results show that the proposed scheme outperforms most of the existing pairwise key establishment schemes in terms of network security, key connectivity and scalability.

Abstract:Many sensors nodes are deployed in a region of concern to detect any potential targets. On the contrary, intelligent target looks for the best path to traverse the sensing field for fear of being detected. This paper focuses on how an intelligent target traverses the sensing field. This traversing problem is modeled, and a number of path-finding algorithms are designed, implemented and evaluated. Different from previous works which assume complete information of the sensing field, it is assumed that the target only can detect part of the sensor nodes deployment. This makes the proposed methods more practical and reasonable. Extensive experiments with a target and a sensor network confirm the validity of the approaches.