Efficient migration for mobile computing in distributed networks

The speed and convenience of the Internet makes it advantageous to online applications. Basing on the elliptic curve cryptosystem, this study proposes a hierarchical mobile agent framework for handling key management and access control problems between mobile agent and host. It raises the security of key management, and also controls access to distributed environment in non-specific network. The proposed method successfully secures the accessing relationship between the mobile agent and the host while economizing the exhaust of storage space. Such an achievement lets the mobile agent operate efficiently, and puts in order a secure execution environment for mobile computing.     

Improved migration for mobile computing in distributed networks

A mobile ad hoc network (MANET) is a special type of wireless network in which a collection of mobile nodes with wireless network interfaces may form a temporary network, without the aids of any fixed infrastructure. Security has become a hot research topic in mobile ad hoc networks. In 1998, Volker and Mehrdad proposed a tree-based key management and access control scheme for the mobile agents to manage rights to access its own resources for the visited mobile nodes. Latter, Huang et al. showed that Volker and Mehrdad's scheme needs a large amount of storage and costs for managing and storing secret keys. Huang et al. further proposed a new and efficient scheme based on the elliptic curve cryptosystems to reduce costs and gain better efficiency. However, there is a security leak inherent in Huang et al.'s scheme that the malicious node can overstep his authority to access unauthorized information. This paper will propose a secure, robust, and efficient hierarchical key management scheme for MANETs. Some practical issues and solutions about dynamic key management are also considered and proposed. As compared with Huang et al.'s scheme, our proposed scheme can provide better security assurance, while requiring smaller key-size, lower computational complexities, and constant key management costs which is independent on the number of the confidential files and the visited nodes.     

JAID: An algorithm for data fusion and jamming avoidance on distributed sensor networks

Mobile Agent (MA) technology has been recently proposed in Wireless Sensor Networks (WSNs) literature to answer the scalability problem of client/server model in data fusion applications. In this paper, we describe the critical role MAs can play in the field of security and robustness of a WSN in addition to data fusion. The design objective of our Jamming Avoidance Itinerary Design (JAID) algorithm is twofold: (a) to calculate near-optimal routes for MAs that incrementally fuse the data as they visit the nodes; (b) in the face of jamming attacks against the WSN, to modify the itineraries of the MAs to bypass the jammed area(s) while not disrupting the efficient data dissemination from working sensors. If the number of jammed nodes is small, JAID only modifies the pre-jamming scheduled itineraries to increase the algorithm’s promptness. Otherwise, JAID re-constructs the agent itineraries excluding the jammed area(s). Another important feature of JAID is the suppression of data taken from sensors when the associated successive readings do not vary significantly. Data suppression also occurs when sensors’ readings are identical to those of their neighboring sensors. Simulation results confirm that JAID enables retrieval of information from the working sensors of partially jammed WSNs and verifies its performance gain over alternative approaches in data fusion tasks.     

Flocking based distributed self-deployment algorithms in mobile sensor networks

In this paper, we address a novel deployment problem in isotropic mobile sensor networks. Sensors are to be relocated uniformly in a region of interest (ROI) centered at a target of interest (TOI) which could be stationary or mobile. With the assumption that relative direction of a sensor to the TOI can be recognized or inferred by devices equipped in the sensor, distributed control algorithms based on first-order and second-order dynamic models are proposed for both stationary and mobile TOI situations. The Lyapunov stabilities and coverage guarantee are provided. To further improve the deployment such as coverage holes inside the network and uniformity of the deployment, four assisted rules are also proposed. Then algorithms proposed for the situation of a stationary TOI are extended to anisotropic sensor networks. Simulations demonstrate the effective performances of the proposed algorithms.     

Multi-rate distributed fusion estimation for sensor networks with packet losses

This paper presents a distributed fusion estimation method for estimating states of a dynamical process observed by wireless sensor networks (WSNs) with random packet losses. It is assumed that the dynamical process is not changing too rapidly, and a multi-rate scheme by which the sensors estimate states at a faster time scale and exchange information with neighbors at a slower time scale is proposed to reduce communication costs. The estimation is performed by taking into account the random packet losses in two stages. At the first stage, every sensor in the WSN collects measurements from its neighbors to generate a local estimate, then local estimates in the neighbors are further collected at the second stage to form a fused estimate to improve estimation performance and reduce disagreements among local estimates at different sensors. Local optimal linear estimators are designed by using the orthogonal projection principle, and the fusion estimators are designed by using a fusion rule weighted by matrices in the linear minimum variance sense. Simulations of a target tracking system are given to show that the time scale of information exchange among sensors can be slower while still maintaining satisfactory estimation performance by using the developed estimation method.     

无线传感器网络下分布式决策融合方法综述

分布式决策融合方法以其成本低廉、可靠性高、生存能力强、带宽要求低等优点而在多传感器检测系统特别是无线传感器网络中具有广阔的应用前景,但是传感器网络具有有限的能量、有限的计算能力、有限的通讯带宽,以及存在无线信道衰落、传输错误和干扰噪声对分布式决策融合理论带来挑战。介绍了分布式检测和决策融合的理论基础,对近年来无线传感器网络下的分布式决策融合理论方法及其研究进展进行了详细的综述,分析并展望了该领域存在的问题和前景,探讨了进一步的研究方向。     

Querying distributed multimedia databases and data sources for sensor data fusion

Sensor data fusion imposes a number of novel requirements on query languages and query processing techniques. A spatial/temporal query language called /spl Sigma/QL has been proposed to support the retrieval and fusion of multimedia information from multiple sources and databases. In this paper we investigate fusion techniques, multimedia data transformations and /spl Sigma/QL query processing techniques for sensor data fusion. Fusion techniques including fusion by the merge operation, the detection of moving objects, and the incorporation of belief values, have been developed. An experimental prototype has been implemented and tested to demonstrate the feasibility of these techniques.     

Joint probabilistic data association in distributed sensor networks

A distributed multitarget tracking problem is considered. The joint probabilistic data association (JPDA) algorithm, which has been successfully used for tracking multiple targets in a cluttered environment, assumes a centralized processing architecture. It assumes that measurements are transmitted to a central site and processed. In some applications, however, it may be desirable for the sensor measurements to be processed at or near the sensors instead of transmitting them to the central processor. The local processed results are then sent over a communication network to be used by other processors. This paper presents a distributed version of the JPDA algorithm which is applicable under such a situation.     

无线传感器网络的一种多层数据融合方案

对一种无线传感器网络路由协议定向扩散作了分析,并针对其局限性提出了一种多层数据融合方案.多层数据融合方案采用多层结构,在数据传输过程中建立节点的属性并进行父亲选择融合和数据分发.实验证明:多层数据融合方案较之定向扩散节约了50%的传输能量,而没有危及网络的可靠性和传输效率.     

无线传感器网络网内数据融合的研究

针对目前无线传感器网络(WSNs)网内数据融合所面临的一些挑战,提出了一种基于无线传感器网络分布式K-平均聚类(DKCWSNs)算法的WSNs节点传感数据的分组策略,并采用基于自适应加权的数据融合方法对分组后的感知数据进行融合处理,从而获得更合理的结果.最后,通过实例验证了该方法的有效性.     

In-network data acquisition and replication in mobile sensor networks

This paper assumes a set of n mobile sensors that move in the Euclidean plane as a swarm. Our objectives are to explore a given geographic region by detecting and aggregating spatio-temporal events of interest and to store these events in the network until the user requests them. Such a setting finds applications in mobile environments where the user (i.e., the sink) is infrequently within communication range from the field deployment. Our framework, coined SenseSwarm, dynamically partitions the sensing devices into perimeter and core nodes. Data acquisition is scheduled at the perimeter, in order to minimize energy consumption, while storage and replication takes place at the core nodes which are physically and logically shielded to threats and obstacles. To efficiently identify the nodes laying on the perimeter of the swarm we devise the Perimeter Algorithm (PA), an efficient distributed algorithm with a low communication complexity. For storage and fault-tolerance we devise the Data Replication Algorithm (DRA), a voting-based replication scheme that enables the exact retrieval of values from the network in cases of failures. We also extend DRA with a spatio-temporal in-network aggregation scheme based on minimum bounding rectangles to form the Hierarchical-DRA (HDRA) algorithm, which enables the approximate retrieval of events from the network. Our trace-driven experimentation shows that our framework can offer significant energy reductions while maintaining high data availability rates. In particular, we found that when failures across all nodes are less than 60%, our framework can recover over 80% of detected values exactly.     

Scalable structure-free data fusion on wireless sensor networks

Recent advancements in sensor technology, wireless networks and consequently wireless sensor networks and the increase in their applications in different fields have led to their great importance. One of the most important challenges of such networks is the distributed management of the huge amount of data produced by sensors in network to reduce data traffic in network and minimize the energy consumption. In this research, a distributed, dynamic fusion algorithm is introduced. Since the proposed method is dynamic, the number of neighbors sending data to a node is not known in advance. So in order to increase the chances of different data to meet, the node waiting time is calculated. By the end of waiting time, the node performs data fusion and sends the fused data to the best neighbor chosen by the proposed best neighbor algorithm. This procedure continues until data reaches the sink. The proposed algorithm, while being scalable and convergent, outperforms similar methods in terms of number of transmissions, traffic load and energy consumption.     

Min-max optimal data encoding and fusion in sensor networks

The paper considers a sensor network whose sensors observe a common quantity and are affected by arbitrary additive bounded noises with a known upper bound. During the experiment, any sensor can communicate only a finite and given number of bits of information to the decision center. The contributions of the particular sensors, the rules of data encoding, decoding, and fusion, as well as the estimation scheme should be designed to achieve the best overall performance in estimation of the observed quantity by the decision center. An optimal algorithm is obtained that minimizes the maximal feasible error. It is shown that it considerably outperforms the algorithm proposed in recent papers in the area and examined only in the idealized case of noiseless sensors.     

一个分布式传感器网络数据访问控制方案的改进

分析了HUR J提出的一个细粒度分布式传感器网络数据访问控制方案,指出其具有抗合谋攻击性和前向保密性问题,并采用委托系统控制器生成更新属性群密钥的方法弥补这两项缺陷。新方案同样支持细粒度的访问控制,安全性更强。     

Energy-efficient routing for mobile data collectors in wireless sensor networks with obstacles

This paper proposes an energy-efficient routing mechanism by introducing intentional mobility to wireless sensor networks (WSNs) with obstacles. In the sensing field, Mobile Data Collectors (MDCs) can freely move for collecting data from sensors. An MDC begins its periodical movement from the base station and finally returns and transports the data to the base station. In physical environments, the sensing field may contain various obstacles. A research challenge is how to find an obstacle-avoiding shortest tour for the MDC. Firstly, we obtain the same size grid cells by dividing the network region. Secondly, according to the line sweep technique, the spanning graph is easily constructed. The spanning graph composed of some grid cells usually includes the shortest search path for the MDC. Then, based on the spanning graph, we can construct a complete graph by Warshall-Floyd algorithm. Finally, we present a heuristic tour-planning algorithm on the basis of the complete graph. Through simulation, the validity of our method is verified. This paper contributes in providing an energy-efficient routing mechanism for the WSNs with obstacles.     

Finding routes in anonymous sensor networks

We consider networks of anonymous sensors and address the problem of constructing routes for the delivery of information from a group of sensors in response to a query by a sink. In order to circumvent the restrictions imposed by anonymity, we rely on using the power level perceived by the sensors in the query from the sink. We introduce a simple distributed algorithm to achieve the building of routes to the sink and evaluate its performance by means of simulations.