Hongli Xu

Bandwidth-Power Aware Cooperative Multipath Routing for Wireless Multimedia Sensor Networks

Cooperative communication is becoming an attractive technology as it can greatly improve the spatial diversity without additional antennas. This novel communication paradigm can effectively reduce power consumption via multi-node cooperation and resource allocation. This paper studies the energy-efficient node-disjoint multi-path routing for a given source-destination pair by joint route construction, relay assignment and power allocation methods. We first define a new bandwidth-power aware cooperative multi-path routing (BP-CMPR) problem, and formally prove its NP-hardness. The paper then presents a polynomial-time heuristic algorithm CMPR to solve the above problem. The algorithm adopts the Suurballes method to find k minimal-weight node-disjoint paths from source to destination on a weighted graph. Then, dynamic programming is used to implement relay assignment and power allocation. The theoretical analysis shows that CMPR can reach approximation factors of 2 and \frac{4}{3} for BP-CMPR under the amplify-and-forward and decode-and-forward schemes respectively. The distributed version of the algorithm DCMPR is also presented for this problem. We also prove that both CMPR and DCMPR construct the same cooperative multi-path routing, and show via simulations that the performance of the proposed scheme is more than 15% better than that of a traditional multi-path routing scheme, and close to the optimal result for BP-CMPR in variety of situations.

Energy-efficient cooperative data aggregation for wireless sensor networks

Recently, cooperative communication mechanism is shown to be a promising technology to improve the transmit diversity only by a single transceiver antenna. Using this communication paradigm, multiple source nodes are able to coordinate their transmissions so as to obtain energy savings. As data aggregation is one of the most important operations in wireless sensor networks, this paper studies the energy-efficient data aggregation problem through cooperative communication. We first define the cooperative data aggregation (CDA) problem, and formally prove that this problem is NP-Hard. Due to the difficult nature of this problem, we propose a heuristic algorithm MCT for cooperative data aggregation. The theoretical analysis shows that this algorithm can reach the approximate performance ratio of 2. Moreover, the distributed implementation DMCT of the algorithm is also described. We prove that both centralized and distributed algorithms can construct the same topology for cooperative data aggregation. The experimental simulations show that the proposed algorithms will decrease the power consumption by about 12.5% and 66.3% compared with PEDAP and PEGASIS algorithms respectively.

Fuzzy-Logic-Based Energy Optimized Routing for Wireless Sensor Networks

Wireless sensor nodes are usually powered by batteries and deployed in unmanned outdoors or dangerous regions. So, constrained energy is a prominent feature for wireless sensor networks. Since the radio transceiver typically consumes more energies than any other hardware component on a sensor node, it is of great importance to design energy optimized routing algorithm to prolong network lifetime. In this work, based on analysis of energy consumption for data transceiver, single-hop forwarding scheme is proved to consume less energy than multihop forwarding scheme within the communication range of the source sensor or a current forwarder, using free space energy consumption model. We adopt the social welfare function to predict inequality of residual energy of neighbors after selecting different next hop nodes. Based on energy inequality, the method is designed to compute the degree of energy balance. Parameters such as degree of closeness of node to the shortest path, degree of closeness of node to Sink, and degree of energy balance are put into fuzzy logic system. Fuzzy-logic-based energy optimized routing algorithm is proposed to achieve multiparameter, fuzzy routing decision. Simulation results show that the algorithm effectively extends the network lifetime and has achieved energy efficiency and energy balance together, compared with similar algorithms.

PPS: Privacy-Preserving Strategyproof Social-Efficient Spectrum Auction Mechanisms

Many spectrum auction mechanisms have been proposed for spectrum allocation problem, and unfortunately, few of them protect the bid privacy of bidders and achieve good social efficiency. In this paper, we propose PPS, a Privacy Preserving Strategyproof spectrum auction framework. We design two schemes based on PPS separately for 1) the single-unit auction model (SUA), where only single channel will be sold in the spectrum market; and 2) the multi-unit auction model (MUA), where the primary user subleases multi-unit channels to the secondary users and each of the secondary users wants to access multi-unit channels either. Since the social efficiency maximization problem is NP-hard in both auction models, we present allocation mechanisms with approximation factors of (1 + ε) and 32 separately for SUA and MUA, and further judiciously design strategyproof auction mechanisms with privacy preserving based on them. Our extensive evaluations show that our mechanisms achieve good social efficiency and with low computation and communication overhead.

Joint relay assignment and power allocation for cooperative communications

In the recent years, cooperative communication is shown to be a promising technology to improve the spatial diversity without additional equipments or antennas. With this communication paradigm, energy can be saved by effective relay assignment and power allocation while achieving the required bandwidth for each transmission pair. Thus, this paper studies the joint relay node assignment and power allocation problem which aims to minimize the total power consumption of the network while providing the efficient bandwidth service. We first analyze the minimum power consumption under the bandwidth requirement for different communication modes. Based on the analytical results, we present a polynomial-time algorithm JRPA to optimally solve this problem. The algorithm first constructs a weighted bipartite graph G based on the given transmission pairs and relay nodes. Then, we adopt the KM method to find out a saturated matching M, and assign the relay nodes to the transmission pairs based on the matching. The optimality of the algorithm is also proved. The simulation results show that JRPA algorithm can save about 34.2% and 18.9% power consumptions compared with the direct transmission and ORA schemes in many situations.

Wireless Sensor Networks for Intensive Irrigated Agriculture

The recent years, achievements in micro-sensor technology and low-power electronics make wireless sensor networks become into realities in applications.In this paper, we basically describe the implementation of the intensive irrigated agriculture monitoring system based on wireless sensor networks.we give some key technologies of wireless sensor networks according as the system performance requirements for this application, longevity and latency.

Joint Virtual MIMO and Data Gathering for Wireless Sensor Networks

Virtual multi-input multi-output (MIMO) or vMIMO is becoming an attractive technology to achieve spatial diversity in wireless networks without using additional antennas, and to reduce power consumption by cooperation among multiple nodes. As data gathering is one of the most important operations in many sensor network applications, this paper studies energy-efficient data gathering in wireless sensor networks using vMIMO. We define the joint vMIMO and data gathering (vMDG) problem, which is NP-hard. We also propose a distributed method called D-vMDG as an approximation algorithm. This algorithm first constructs a tree-like topology by taking the unique features of vMIMO into account. Then, an energy-efficient routing protocol based on dynamic programming is proposed for each node on the constructed topology. Our theoretical analysis shows that D-vMDG can achieve an approximation ratio of O(1). Our simulations show that D-vMDG decreases the energy consumption by 81 and 36 percent compared to the well-known MDT [26] and MIMO-LEACH [19] algorithms respectively.

Topology control for delay-constraint data collection in wireless sensor networks

Data collection is one of the most important operations in wireless sensor networks. Many practical applications require the real-time data transmission, such as monitoring, tracking, etc. In this paper, we import and define the topology control problem for delay-constraint data collection (TDDC), and then formalize this problem into an integer programming problem. As NP-Hardness of this problem, we present a load-aware power-increased topology control algorithm (namely LPTC) to heuristically solve the problem. The theoretical analysis shows that this algorithm can reach O(1)-approximation ratio for the linear networks. And we also analyze the impact of the delay-constraint on the worst-case for the planar networks. Moreover, this paper designs two localized algorithms, called as SDEL and DDEL, based on the area division for TDDC problem. The experimental results show that LPTC algorithm can save at least 17% power consumptions compared with HBH algorithm in many situations.

An Adaptive Collision-Free MAC protocol based on TDMA for Inter-Vehicular communication

Inter-Vehicular communication is considered to be a promising way to improve traffic safety. Among this, it is a key technology to delivery urgent messages and periodical beacons to neighbors successfully. In this paper, we propose an Adaptive Collision-Free MAC (ACFM) protocol tailored to vehicular networks, based on dynamic TDMA mechanism. In our protocol, RoadSide Units (RSUs) are exploited to schedule time slots assignment and disseminate control information, while the data are spread among vehicles. Each RSU maintains a dynamical slots assignment cycle for vehicles in its coverage adaptively. A cycle consists of N frames, where N varies from 1 to 5 according to the number of vehicles. Under the scenario of light traffic, ACFM controls the excessive increase of unassigned slots through shrinking slots assignment cycle frame by frame. When there are a mass of vehicles on roads, ACFM provides more available slots by expanding cycle which ensures the fairness of channel access for every vehicle. Channel utilization and fairness can be achieved together in ACFM We implement the protocol on NS-2 for a comparative evaluation against conventional protocols under realistic VANET scenarios. Simulation results show that the ACFM scheme outperforms the conventional protocols in terms of packet loss ratio and delay.

A mechanism for reducing flow tables in software defined network

The software defined network (SDN) has been developing tremendously in recent years. Numerous studies are proposed on the performance of SDN in academia. The idea of programmable network which is the foundation of SDN ensures dynamic network management by separating the control plane away from the network switches. The focus of this paper is the flow tables size in OpenFlow switches which is a significant bottleneck in SDNs practical application. We propose a mechanism named “Flow Table Reduction Scheme”(FTRS) for reducing the flow table size and maintaining the omnipotent controllers functions at the same time. We test the performance of FTRS both in simulation and experiment and the results show that FTRS is able to reduce 98% at most of the size of flow table with no impact on networks normal functions.