15517812
Service Composition in Service-Oriented Wireless Sensor Networks with Persistent Queries
Service-oriented wireless sensor network (WSN) has been recently proposed as an architecture to rapidly develop applications in WSNs. In WSNs, a query task may require a set of services and may be carried out repetitively with a given frequency during its lifetime. A service composition solution shall be provided for each execution of such a persistent query task. Due to the energy saving strategy, some sensors may be scheduled to be in sleep mode periodically. Thus, a service composition solution may not always be valid during the lifetime of a persistent query. When a query task needs to be conducted over a new service composition solution, a routing update procedure is involved which consumes energy. In this paper, we study service composition design which minimizes the number of service composition solutions during the lifetime of a persistent query. We also aim to minimize the total service composition cost when the minimum number of required service composition solutions is derived. A greedy algorithm and a dynamic programming algorithm are proposed to complete these two objectives respectively. The optimality of both algorithms provides the service composition solutions for a persistent query with minimum energy consumption.
9143022
Data fusion improves the coverage of wireless sensor networks
Wireless sensor networks (WSNs) have been increasingly available for critical applications such as security surveillance and environmental monitoring. An important performance measure of such applications is sensing coverage that characterizes how well a sensing field is monitored by a network. Although advanced collaborative signal processing algorithms have been adopted by many existing WSNs, most previous analytical studies on sensing coverage are conducted based on overly simplistic sensing models (e.g., the disc model) that do not capture the stochastic nature of sensing. In this paper, we attempt to bridge this gap by exploring the fundamental limits of coverage based on stochastic data fusion models that fuse noisy measurements of multiple sensors. We derive the scaling laws between coverage, network density, and signal-to-noise ratio (SNR). We show that data fusion can significantly improve sensing coverage by exploiting the collaboration among sensors. In particular, for signal path loss exponent of k (typically between 2.0 and 5.0), rho_f=O(rho_d^(1-1/k)), where rho_f and rho_d are the densities of uniformly deployed sensors that achieve full coverage under the fusion and disc models, respectively. Our results help understand the limitations of the previous analytical results based on the disc model and provide key insights into the design of WSNs that adopt data fusion algorithms. Our analyses are verified through extensive simulations based on both synthetic data sets and data traces collected in a real deployment for vehicle detection.
8394501
Handover Cost Optimization in Traffic Management for Multi-homed Mobile Networks
In this paper, we study the traffic management problem for multi-homed mobile networks with the objective of minimizing the overall handover cost. Two different traffic distribution modes are considered in our study: the Fractional Flow Assignment (FFA) mode which assumes the bandwidth demand from one connection is infinitely splittable and can be assigned to different wireless access networks, and the Integral Flow Assignment (IFA) mode which assumes that at any time the bandwidth demand from each connection can only be assigned to a single wireless network. We show that the general FFA problem and the IFA problem are both NP-hard and propose optimal solutions to the four special cases of the FFA problem and heuristic solutions to the general FFA problem and the IFA problem. Extensive simulations are conducted to verify the impact of the capacity-demand ratio on the performance of the proposed solutions.
3020928
Mobility-Assisted Spatiotemporal Detection in Wireless Sensor Networks
Wireless sensor networks (WSNs) deployed for mission-critical applications face the fundamental challenge of meeting stringent spatiotemporal performance requirements using nodes with limited sensing capacity. Although advance network planning and dense node deployment may initially achieve the required performance, they often fail to adapt to the unpredictability of physical reality. This paper explores efficient use of mobile sensors to address the limitations of static WSNs in target detection. We propose a data fusion model that enables static and mobile sensors to effectively collaborate in target detection. An optimal sensor movement scheduling algorithm is developed to minimize the total moving distance of sensors while achieving a set of spatiotemporal performance requirements including high detection probability, low system false alarm rate and bounded detection delay. The effectiveness of our approach is validated by extensive simulations based on real data traces collected by 23 sensor nodes.
17259450
Routing and wavelength assignment for core-based tree in WDM networks
In this paper, we address the routing and wavelength assignment problem for the core-based tree (CBT) service in a wavelength-division-multiplexing (WDM) network, where k sources need to send data to a common core node. We formally model the problem as a problem of finding k shortest lightpaths from sources to the core with the constraint of wavelength collision free. To address different objectives, we define and study several subproblems. For the feasibility and the minimum total cost problems of k shortest lightpaths, we show how the classical network flow algorithms can be modified and applied efficiently on the network flow model constructed on the transformed wavelength graph. For the minimum max-cost and the constrained feasibility problems, we prove their NP-completeness and propose two efficient heuristic algorithms. Simulation results show that the proposed heuristic algorithms achieve performance very close to the calculated lower bounds.
4792
Fast Sensor Placement Algorithms for Fusion-Based Target Detection
Mission-critical target detection imposes stringent performance requirements for wireless sensor networks, such as high detection probabilities and low false alarm rates. Data fusion has been shown as an effective technique for improving system detection performance by enabling efficient collaboration among sensors with limited sensing capability. Due to the high cost of network deployment, it is desirable to place sensors at optimal locations to achieve maximum detection performance. However, for sensor networks employing data fusion, optimal sensor placement is a non-linear optimization problem with prohibitive computational complexity. In this paper, we present fast sensor placement algorithms based on a probabilistic data fusion model. Simulation results show that our algorithms can meet the desired detection performance with a small number of sensors while achieving up to 7-fold speedup over the optimal algorithm.
42010730
Cross-layer Routing Design in Cognitive Radio Networks by Colored Multigraph Model
In this paper, the cross-layer design routing in cognitive radio(CR) networks is studied. We propose a colored multigraph based model for the temporarily available spectrum bands, called spectrum holes in this paper. Based on this colored multigraph model, a polynomial time algorithm with complexity O(n2) is also proposed to develop a routing and interface assignment, where n is the number of nodes in a CR network. Our algorithm optimizes the hop number of routing, meanwhile, the adjacent hop interference (AHI) is also optimized locally.
2128602
Programming Overlay Networks with Overlay Sockets
The emergence of application-layer overlay networks has inspired the development of new network services and applications. Research on overlay networks has focused on the design of protocols to maintain and forward data in an overlay network, however, less attention has been given to the software development process of building application programs in such an environment. Clearly, the complexity of overlay network protocols calls for suitable application programming interfaces (APIs) and abstractions that do not require detailed knowledge of the overlay protocol, and, thereby, simplify the task of the application programmer. In this paper, we present the concept of an overlay socket as a new programming abstraction that serves as the end point of communication in an overlay network. The overlay socket provides a socket-based API that is independent of the chosen overlay topology, and can be configured to work for different overlay topologies. The overlay socket can support application data transfer over TCP, UDP, or other transport protocols. This paper describes the design of the overlay socket and discusses API and configuration options. The overlay socket has been used to develop a variety of applications, from multicast-file transfer programs, to multicast video streaming systems.
5372457
Traffic Engineering with AIMD in MPLS Networks
We consider the problem of allocating bandwidth to competing flows in an MPLS network, subject to constraints on fairness, efficiency, and administrative complexity. The aggregate traffic between a source and a destination, called a flow, is mapped to label switched paths (LSPs) across the network. Each flow is assigned a preferred ('primary') LSP, but traffic may be sent to other ('secondary') LSPs. Within this context, we define objectives for traffic engineering, such as fairness, efficiency, and preferred flow assignment to the primary LSP of a flow ('Primary Path First', PPF). We propose a distributed, feedback-based multipath routing algorithm that attempts to apply additive-increase and multiplicative-decrease (AIMD) to implement our traffic engineering objectives. The new algorithm is referred to as multipath-AIMD. We use ns-2 simulations to illustrate the fairness criteria and PPF property of our multipath-AIMD scheme in an MPLS network.