He Huang

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.

True-MCSA: A Framework for Truthful Double Multi-Channel Spectrum Auctions

Spectrum auctions motivate existing spectrum owners (as sellers) to lease their selected idle channels to new spectrum users (as buyers) who need the spectrum desperately. The most significant requirement is how to make the auctions economic-robust (truthful in particular) while enabling spectrum reuse. Furthermore, in practice, both sellers and buyers would require to trade multiple channels at one time, while guaranteeing their individual profitability. Unfortunately, existing designs can not meet all these requirements simultaneously. We address these requirements by proposing True-MCSA, a framework for truthful double multi-channel spectrum auctions. True-MCSA introduces novel virtual buyer group (VBG) splitting and bidding algorithms, and applies a proper winner determination and pricing mechanism to achieve truthfulness and other economic properties, meanwhile successfully dealing with multi-channel requests from both buyers and sellers and improving spectrum utilization. Our experiments show that the auction efficiency is impacted by the economic factors with efficiency degradations within 30%, under different settings. Furthermore, the experimental results indicate that we can improve the auction efficiency by choosing a proper bidding algorithm and using a positive base bid. True-MCSA makes an important contribution on enabling spectrum reuse to improve auction efficiency in multi-channel cases.

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.

Truthful Auction Mechanisms with Performance Guarantee in Secondary Spectrum Markets

We study a spectrum auction problem where each request from new spectrum users has spatial, temporal, and spectral features. Our goal is to design truthful auction mechanisms that maximize either the overall social efficiency of new users (a.k.a buyers) or the revenue of the spectrum owner (a.k.a seller). Given that the optimal conflict-free spectrum allocation problem is NP-hard, this paper proposes a series of near-optimal auction mechanisms based on the following approximation techniques: linear programming (LP) relaxation, randomized rounding, derandomized rounding, monotone derandomization, and Lavi-Swamy method. Comparing with the prior art, we make two significant advances: First, our auction mechanisms are not only truthful but also provide theoretically-provable performance guarantee, an important feature that existing work under the same auction model does not have. Second, our auction mechanisms support both spatial and temporal spectral reuse, which makes the problem more challenging than existing work that deals with only spatial or temporal reuse. We perform extensive simulations to study the performance of the proposed mechanisms, and the simulation results corroborate our theoretical analysis.

Cluster-based load balancing multi-path routing protocol in wireless sensor networks

For extending the lifetime of sensor networks by improving load balancing in wireless sensor networks, the cluster-based multi-path routing protocol, CLBM, has been studied in this paper. In CLBM, theory of space and time localization has been introduced in the process of cluster head reselecting, cluster node will select the cluster head according to residual energy and the nearest distance between the node and the event center area. The cluster head can reduce the energy consumption of itself by sending the data to the nearest node of multi-path routing; while for cluster node, consulting with its child node can reduce the energy consumption of whole networks. It can be demonstrated by simulation experiments that CLBM protocol basically achieves the load balancing of networks so as to extending the network lifetime efficiently.

Truthful Multi-unit Double Auction for Spectrum Allocation in Wireless Communications

In this paper, we propose a truthful multi-unit double auction scheme for the scenarios that multiple buyers/sellers have different demands to buy/sell, which involves a series of bid-related buyer group construction and winner determination strategies. In the analysis, we show the correctness and effectiveness of the proposed scheme and prove that it improves the spectrum reusability and is truthful. To the best of our knowledge, it is the first multi-unit double auction approach for wireless spectrum allocation.

Optimal relay assignment for fairness in wireless cooperative networks

Under this cooperative communication, the selection of relay node significantly affects the performance of wireless networks. The previous researches optimised the Max-Min Fairness (MF), which may drastically decrease the network throughput. Thus, this paper studies the fairness-aware relay assignment to improve the network throughput. First, we develop the PFRA algorithm, which assigns the relays by saturated bipartite matching, to reach the proportional fairness. Next, a distributed version of Proportional Fairness Relay Assignment (PFRA) algorithm is also proposed. Moreover, lexicographical Max-Min fairness is achieved by Lexicographical Fairness Relay Assignment (LFRA) algorithm. We formally prove the optimality of above three algorithms. The experimental results show the efficiency of the proposed algorithms.

Truthful Auction for Resource Allocation in Cooperative Cognitive Radio Networks

Cooperative cognitive radio network (CCRN) is a promising paradigm to increase spectrum utilization and exploit spatial diversity. The allocation of two related resources, i.e. spectrum and relay nodes, plays a fundamental role in the performance of CCRNs. However, previous works either lack of incentives for both primary users (PUs) and relay nodes to participate in or consider spectrum auction and relay auction separately. In this paper, we consider a static cooperative cognitive radio network scenario with several PUs and multiple secondary user coteries, each of which consists of a set of secondary users who are interested in sharing the same secondary relay node. We model the problem of joint spectrum allocation and relay allocation as a hierarchical auction and propose TERA, which is the first Truthful auction mechanism for Efficient Resource Allocation in CCRNs. We show that TERA satisfies critical economic properties such as truthful, individual rationality, budget balance, supply limits and computational efficiency. Furthermore, we theoretically prove TERA can achieve near-optimal revenue with high probability. Finally, extensive simulation results show that TERA is efficient and able to improve the utility of PUs and relay nodes significantly up to 125% and 151% respectively.

Near-optimal truthful spectrum auction mechanisms with spatial and temporal reuse in wireless networks

In this work, we study spectrum auction problem where each spectrum usage request has spatial, temporal, and spectral features. After receiving bid requests from secondary users, and possibly reserve price from primary users, our goal is to design truthful mechanisms that will either optimize the social efficiency or optimize the revenue of the primary user. As computing an optimal conflict-free spectrum allocation is an NP-hard problem, in this work, we design near optimal spectrum allocation mechanisms separately based on the techniques: derandomized allocation from integer programming formulation, and its linear programming (LP) relaxation. We theoretically prove that 1) our derandomized allocation methods are monotone, thus, implying truthful auction mechanisms; 2) our derandomized allocation methods can achieve a social efficiency or a revenue that is at least

Cooperative Data Processing Algorithm Based on Mobile Agent in Wireless Sensor Networks

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