Xiaozong Yang

EEMC: An energy-efficient multi-level clustering algorithm for large-scale wireless sensor networks

Wireless sensor networks can be used to collect surrounding data by multi-hop. As sensor networks have the limited and not rechargeable energy resource, energy efficiency is an important design issue for its topology. In this paper, we propose a distributed algorithm, EEMC (energy-efficient multi-tier clustering), that generates multi-tier clusters for long-lived sensor networks. EEMC terminates in O(log logN) iterations given N nodes, incurs low energy consumption and latency across the network. Simulation results demonstrate that our proposed algorithm is effective in prolonging the large-scale network lifetime and achieving more power reductions

CNPGSDP: an efficient group-based service discovery protocol for MANETs

The ability to discover services is the major prerequisite for effective usability of MANETs. Group-based Service Discovery (GSD) protocol is a typical service discovery protocol for MANETs. However, because of large redundant packet transmissions, its packet overhead is high. In this paper, in light of GSD, we propose a new service discovery protocol for Mobile Ad-Hoc Networks (MANETs): Candidate Node Pruning enhanced Group-based Service Discovery Protocol (CNPGSDP). In CNPGSDP, two schemes are introduced to enhance GSD: Broadcast Simulated Unicast (BSU) and Candidate Node Pruning (CNP). In BSU, several unicast request packets are replaced with one request packet transmitted in broadcast mode with all unicast receivers enclosed. CNP further reduces the number of request packets by reducing the number of candidate nodes. Mathematical analysis and simulation tests both show that CNPGSDP is a very effective, efficient, and prompt service discovery protocol for MANETs.

ECCRA: An energy-efficient coverage and connectivity preserving routing algorithm under border effects in wireless sensor networks

Wireless sensor networks can be used to monitor the interested region using multi-hop communication. Coverage is a primary metric to evaluate the monitoring capacity. Connectivity also should be guaranteed so that the sink node can receive all sensed data for future processing. In this paper, combining these two problems, we study the connected, coverage problem given a specific network coverage ratio under border effects. We consider the scenario where the sensor nodes are distributed in a circle-shaped region uniformly. We first derive the network coverage provided by N sensor nodes by the mathematical formulae exactly. The lower bound of the network connectivity probability is also derived. Since sensor nodes are equipped with energy-limited batteries, energy conservation in such networks is of paramount importance to prolong the network lifetime. Accordingly, we then propose a location-independent, energy-efficient routing algorithm ECCRA which achieves the required network coverage and sensor connectivity simultaneously. The extensive simulation results demonstrate that our algorithm is correct and effective.

PCPGSD: An enhanced GSD service discovery protocol for MANETs

Group based Service Discover protocol (GSD) service discovery protocol is a well-known service discovery protocol for MANETs. However, because of some obviously redundant transmissions, its packet overhead is very high. Hence, in this paper, three mechanisms are introduced to reduce its the packet overhead. The three mechanisms are PFCN (Pruning of Far Candidate Nodes), CRN (Combining of Relay Nodes), and PRN (Piggybacking of Relay Nodes). Hence, the enhanced protocol is called PCPGSD (PFCN, CRN, and PRN enhanced GSD). Mathematical analysis and simulation tests both show that PFCN, CRN, and PRN can reduce packet overhead greatly. Simulation results show that PCPGSD outperforms some other typical service discovery protocols up to several times.

An ad hoc multicast protocol based on passive data acknowledgement

An ad hoc network is a multi-hop wireless network of mobile nodes without fixed infrastructure. Its limited bandwidth and frequently changing topology require that its protocol should be robust, simple and energy conserving. In this paper, we propose a new ad hoc multicast protocol based on Passive Data Acknowledgement (PDAODMRP). PDAODMRP has the following contributions: (1) it knows the status of its downstream forwarding nodes by route information collected from data packets instead of BEACON signal of MAC layer, and reduces the waste of wireless bandwidth created by the BEACON signal; (2) it adopts a new route information collection from data packets to reduce the CPU usage of data route information collection; and (3) it adopts a dynamic local route maintenance to enforce its local route maintenance. From simulation results, it can be seen that PDAODMRP has low control overhead and low data delivery delay.

Energy Efficient Non-uniform Clustering Division Scheme in Wireless Sensor Networks

Wireless sensor networks can be used to monitor the interested region by multi-hop communication. Since sensor nodes are equipped with energy-limited batteries, energy conservation in such networks is of paramount importance in order to prolong the network lifetime. In this paper, considering the constrained radio range of node, we propose an energy efficient clustering division scheme from the viewpoint of energy consumption. The difference between our scheme and previous schemes is that ours is a non-uniform clustering hierarchy. With the algorithm that is proposed by this paper, we can divide the cluster into multiple non-uniform concentric rings and obtain the optimal thickness of each ring. Motivated by the derived results, every sensor node can adjust its radio range for transmission. Our extensive simulation results indicate that the proposed non-uniform clustering division scheme outperforms the conventional uniform clustering division schemes in terms of energy consumption and lifetime. The future research that should be explored is also discussed finally.

Energy of Flat VS Clustering Wireless Sensor Networks: A Comparative Study

Wireless sensor networks (WSNs) can be used to collect surrounding data by multi-hop. As sensor networks have the limited and not rechargeable energy resource, energy efficiency is an important design issue for its topology. In this paper, we derive the exact mathematical expression for the flat and clustering schemes, respectively. Then the energy consumption of different schemes are compared. Motivated by the comparison, we propose an energy-efficient multi-tier clustering algorithm EEMC. EEMC terminates in O(log logN) iterations given N nodes, incurs low energy consumption across the network. Simulation results demonstrate that our proposed algorithm is effective in prolonging the large-scale network lifetime and achieving more power reductions.

Lifetime Analysis of Data Aggregation Tree with Unreliable Sensor Node

Energy consumption and reliability are two critical issues in wireless sensor networks (WSNs). What is the length of lifetime of a WSN in an unreliable environment is our focus. In this paper, the clustering scheme is introduced firstly. A data aggregation tree model is formed in the periodic data collection application. Based on this model, the energy consumption and reliability issues are analyzed, which are both related to the lifetime of a WSN. Accordingly we obtain the lifetime T of the network, which is defined as the time after which the probability of connectivity is less than 1 - epsiv. Here epsiv is a small parameter. Simulation results demonstrate that our analysis is correct and effective.

Coverage And Connectivity Problems Under Border Effects In Wireless Sensor Networks

Abstract Wireless sensor networks can be used to monitor the interested region by multi-hop communication. Coverage is a primary metric to evaluate the capacity of monitoring. In this paper, we focus on the coverage issue under border effects, where the sensor nodes are distributed in acircle-shaped region randomly. Under this scenario, the expected coverage of the sensor node and the total network coverage provided by n sensor nodes are derived accurately by probability. These fmdings are useful to determine the related parameters (i.e., sensing range, number of sensor nodes and radius of monitored region) for a specific network coverage ratio. Besides, to guarantee the collected data to be arrived at the sink node, the lower bound of network connectivity probability is also calculated when border effects are considered. Simulation results demonstrate that our analysis is correct and effective.