Weifa Liang

Constructing minimum-energy broadcast trees in wireless ad hoc networks

In this paper we assume that a multihop wireless network (also called a wireless ad hoc network) consists of nodes whose transmitting powers are finitely adjustable. We consider two fundamental problems related to power consumption in this kind of network. One is the minimum-energy broadcast tree problem, which broadcasts a message from a source node to all the other nodes in the network such that the summation of transmission powers at all nodes is minimized; and another is the minimum-energy multicast tree problem, which multicasts a message from a source node to the nodes in a given subset of nodes such that the summation of the transmission powers at all involved nodes is minimized.We first show the minimum-energy broadcast tree problem is NP-complete. We then present an approximate algorithm for the problem in a general setting, which delivers an approximate solution with a bounded performance guarantee. The algorithm takes O((k+1)1/εn3/ε time, where n is the number of nodes in the wireless network, k is the number of power levels at each node, and ε is constant with 0⁢ε&xie; 1. For a special case of the problem where every node is equipped with the same type of battery, we propose an approximate algorithm which has a better performance ratio than that in the general case setting, and the algorithm takes O(kn2 log n) time. We finally extend the technique for the minimum-energy broadcast tree problem to solve the minimum-energy multicast tree problem, which leads to a similar result. The technique adopted in this paper is to reduce the minimum-energy broadcast (multicast) tree problem on a wireless ad hoc network to an optimization problem on an auxiliary weighted graph, and solve the optimization problem on the auxiliary graph which in turn gives an approximate solution for the original problem.

Online Data Gathering for Maximizing Network Lifetime in Sensor Networks

Energy-constrained sensor networks have been deployed widely for monitoring and surveillance purposes. Data gathering in such networks is often a prevalent operation. Since sensors have significant power constraints (battery life), energy efficient methods must be employed for data gathering to prolong network lifetime. We consider an online data gathering problem in sensor networks, which is stated as follows: assume that there is a sequence of data gathering queries, which arrive one by one. To respond to each query as it arrives, the system builds a routing tree for it. Within the tree, the volume of the data transmitted by each internal node depends on not only the volume of sensed data by the node itself, but also the volume of data received from its children. The objective is to maximize the network lifetime without any knowledge of future query arrivals and generation rates. In other words, the objective is to maximize the number of data gathering queries answered until the first node in the network fails. For the problem of concern, in this paper, we first present a generic cost model of energy consumption for data gathering queries if a routing tree is used for the query evaluation. We then show the problem to be NP-complete and propose several heuristic algorithms for it. We finally conduct experiments by simulation to evaluate the performance of the proposed algorithms in terms of network lifetime delivered. The experimental results show that, among the proposed algorithms, one algorithm that takes into account both the residual energy and the volume of data at each sensor node significantly outperforms the others

Prolonging Network Lifetime via a Controlled Mobile Sink in Wireless Sensor Networks

In this paper we explore the mobility of a mobile sink in a wireless sensor network (WSN) to prolong the network lifetime. Since the mechanical movement of mobile sink is driven by petrol and/or electricity, the total travel distance of the mobile sink should be bounded. To minimize the data loss during the transition of the mobile sink from its current location to its next location, its moving distance must be restricted. Also, considering the overhead on a routing tree construction at each sojourn location of the mobile sink, it is required that the mobile sink sojourns for at least a certain amount of time at each of its sojourn locations. The distance constrained mobile sink problem in a WSN is to find an optimal sojourn tour for the mobile sink such that the sum of sojourn times in the tour is maximized, subject to the above mentioned constraints. In this paper we first formulate the problem as a mixed integer linear programming (MILP). Due to its NP-hardness, we then devise a novel heuristic for it. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithm in terms of network lifetime. The experimental results demonstrate that the solution delivered by the proposed heuristic is nearly optimal which is comparable with the one by solving the MILP formulation but with much shorter running time.

Approximate minimum-energy multicasting in wireless ad hoc networks

A wireless ad hoc network consists of mobile nodes that are equipped with energy-limited batteries. As mobile nodes are battery-operated, an important issue in such a network is to minimize the total power consumption for each operation. Multicast is one of fundamental operations in any modern telecommunication network including wireless ad hoc networks. Given a multicast request consisting of a source node and a set of destination nodes, the problem is to build a minimum-energy multicast tree for the request such that the total transmission power consumption in the tree is minimized. Since the problem in a symmetric wireless ad hoc network is NP-complete, we instead devise an approximation algorithm with provable approximation guarantee. The approximation of the solution delivered by the proposed algorithm is within a constant factor of the best-possible approximation achievable unless P = NP.

Approximate coverage in wireless sensor networks

Recent advances in microelectronic technology have made it possible to construct compact and inexpensive wireless sensors. Sensor networks have received significant attention due to their potential applications from civil to military domains. Since sensors in sensor networks are equipped with energy-limited batteries, energy conservation in such networks is of paramount importance in order to prolong the network lifetime. Sensing coverage and sensor connectivity in sensor networks are two fundamental issues, which have been extensively addressed in the literature, and most existing work on sensing coverage has focused on the (connected) full coverage problem that aims to cover the entire monitored region using the minimum number of sensors. However, in some application scenarios, full coverage is either impossible or unnecessary and a partial coverage with a certain degree guarantee is acceptable. In this paper, we study the connected coverage problem with a given coverage guarantee. We first introduce the partial coverage concept and analyze its properties for the first time in order to prolong the network lifetime. Due to NP-hardness of the concerned problem, we then present a heuristic algorithm which takes into account the partial coverage and sensor connectivity simultaneously. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithm

Minimum-energy all-to-all multicasting in wireless ad hoc networks

A wireless ad hoc network consists of mobile nodes that are powered by batteries. The limited battery lifetime imposes a severe constraint on the network performance, energy conservation in such a network thus is of paramount importance, and energy efficient operations are critical to prolong the lifetime of the network. All-to-all multicasting is one fundamental operation in wireless ad hoc networks, in this paper we focus on the design of energy efficient routing algorithms for this operation. Specifically, we consider the following minimum-energy all-to-all multicasting problem. Given an all-to-all multicast session consisting of a set of terminal nodes in a wireless ad hoc network, where the transmission power of each node is either fixed or adjustable, assume that each terminal node has a message to share with each other, the problem is to build a shared multicast tree spanning all terminal nodes such that the total energy consumption of realizing the all-to-all multicast session by the tree is minimized. We first show that this problem is NP-complete. We then devise approximation algorithms with guaranteed approximation ratios. We also provide a distributed implementation of the proposed algorithm. We finally conduct experiments by simulations to evaluate the performance of the proposed algorithm. The experimental results demonstrate that the proposed algorithm significantly outperforms all the other known algorithms.

Materialized view selection under the maintenance time constraint

A data warehouse is a data repository which collects and maintains a large amount of data from multiple distributed, autonomous and possibly heterogeneous data sources. Often the data is stored in the form of materialized views in order to provide fast access to the integrated data. One of the most important decisions in designing a data warehouse is the selection of views for materialization. The objective is to select an appropriate set of views that minimizes the total query response time with the constraint that the total maintenance time for these materialized views is within a given bound. This view selection problem is totally different from the view selection problem under the disk space constraint. In this paper the view selection problem under the maintenance time constraint is investigated. Two efficient, heuristic algorithms for the problem are proposed. The key to devising the proposed algorithms is to define good heuristic functions and to reduce the problem to some well-solved optimization problems. As a result, an approximate solution of the known optimization problem will give a feasible solution of the original problem

Optimal Cloudlet Placement and User to Cloudlet Allocation in Wireless Metropolitan Area Networks

Mobile applications are becoming increasingly computation-intensive, while the computing capability of portable mobile devices is limited. A powerful way to reduce the completion time of an application in a mobile device is to offload its tasks to nearby cloudlets, which consist of clusters of computers. Although there is a significant body of research in mobile cloudlet offloading technology, there has been very little attention paid to how cloudlets should be placed in a given network to optimize mobile application performance. In this paper we study cloudlet placement and mobile user allocation to the cloudlets in a wireless metropolitan area network (WMAN). We devise an algorithm for the problem, which enables the placement of the cloudlets at user dense regions of the WMAN, and assigns mobile users to the placed cloudlets while balancing their workload. We also conduct experiments through simulation. The simulation results indicate that the performance of the proposed algorithm is very promising.

Network lifetime maximization in sensor networks with multiple mobile sinks

In this paper we deal with the network lifetime maximization problem under multiple mobile sink environments, namely, the h-hop-constrained multiple mobile sink problem, which is defined as follows. Given a stationary sensor network with K mobile sinks that traverse and sojourn in a given space of locations in the monitoring area, assume that the total travel distance of each sink is bounded by a given value L and the maximum number of hops from each sensor to a sink is bounded by an integer h ≥ 1, the problem is to find an optimal trajectory for each mobile sink and determine the sojourn time at each sojourn location in the trajectory such that the network lifetime is maximized. We first formulate this problem as a joint optimization problem consisting of finding an optimal trajectory and determining the sojourn time at each chosen location. We then show that the problem is NP-hard. We instead devise a novel three-stage heuristic, which consists of calculating the sojourn time profile at each potential sojourn location, finding a high-quality trajectory for each mobile sink, and determining the actual sojourn time at each sojourn location. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithm in terms of network lifetime. We also investigate the impact of constraint parameters on the network lifetime. The experimental results demonstrate that the performance of the proposed heuristic is highly comparable to the optimal one, and the ratios of network lifetime of the proposed algorithm to the optimal network lifetime are ranged from 56% to 93%.

Approximation Algorithms for Capacitated Minimum Forest Problems in Wireless Sensor Networks with a Mobile Sink

To deploy a wireless sensor network for the purpose of large-scale monitoring, in this paper, we propose a heterogeneous and hierarchical wireless sensor network architecture. The architecture consists of sensor nodes, gateway nodes, and mobile sinks. The sensors transmit their sensing data to the gateway nodes for temporary storage through multihop relays, while the mobile sinks travel along predetermined trajectories to collect data from nearby gateway nodes. Under this paradigm of data gathering, we formulate a novel constrained optimization problem, namely, the capacitated minimum forest (CMF) problem, for the decision version of which we first show NP-completeness. We then devise approximation algorithms and provide upper bounds for their approximation ratios. We finally evaluate the performance of the proposed algorithms through experimental simulation. In our experiments, the approximation ratio delivered by the proposed algorithms is always less than 2. In the case of arbitrary gateway capacities, this contrasts our theoretical results which show that the approximation ratio is at most linear in the number of gateways. Our experiments thus indicate that for realistic inputs, our worst case analysis of the approximation ratio is very conservative. The proposed algorithms are the first approximation algorithms for the CMF problem, and our techniques may be applicable to other constrained optimization problems beyond wireless sensor networks.