Search

Peer-to-peer (P2P) services such as mobile P2P transmissions and resource sharing, provide efficient methods to deliver data without the deployment of any central server. Nevertheless, the free-riding phenomenon inherit in such services presses a need for incentive mechanisms to stimulate contributions of data transmissions or sharing. As a result, it is imperative to answer the following questions: whether, and if so to what extent, an incentive mechanism can invoke such contributions? To answer these questions, we employ an $n$ n -player continuous quantum game model to analyze the general extrinsic incentive mechanisms as well as the reputation-based incentive mechanisms, a typical class of extrinsic incentive mechanisms. We focus on studying the extrinsic incentive mechanisms in this paper due to their wide scope of applications stemming from the fact that they promote cooperative behaviors by offering rewards rather than depending on the internal bounds (e.g., social ties) among peers, which may not always exist between any pair of peers. To the best of our knowledge, we are the first to analyze the extrinsic incentive mechanisms for P2P services from a quantum game perspective. Such a perspective is adopted because the extended strategy space in the quantum game broadens the range for searching optimal strategies and the introduction of entanglement makes the proposed analytical frameworks more practical due to the consideration of the peers’ relationships imposed by the rewards in extrinsic incentive mechanisms. Our quantum game-based analytical framework is generic because it is compatible with classic game-based schemes. The analytical results can provide a straightforward insight on evaluating the potential of the extrinsic incentive mechanisms and can serve as important references for designing new extrinsic incentive mechanisms. [ABSTRACT FROM AUTHOR]

In mobile ad-hoc cognitive radio networks (CRNs), end-to-end paths with available spectrum bands for secondary users may exist temporarily, or may never exist, due to the dynamism of the primary user activities. Traditional CRN routing algorithms, which typically ignore the intermittent connectivity of network topology, and traditional mobility-assisted routing algorithms, which generally overlook the spectrum availability, are obviously unsuitable. To tackle this challenge, we propose a Mobility-Assisted Routing algorithm with Spectrum Awareness (MARSA) to select relays based on not only the probability that a node meets the destination but also the chance at which there exists at least one available channel when they meet. To the best of our knowledge, this paper is the first to bring the idea of mobility-assisted routing to deal with the intermittently connected attribute of mobile ad-hoc CRNs, and the first to enhance the mobility-assisted routing by considering the temporal , spatial, and spectrum domains at the same time. Our simulation results demonstrate the superiority of MARSA over traditional algorithms in intermittently connected mobile CRNs. [ABSTRACT FROM AUTHOR]

Traditional spectrum sensing methods require that a secondary user (SU) senses the spectrum at the beginning of each time slot. A closer look at the network activities of a cognitive radio network reveals that the access pattern of a primary user (PU) typically consists of a succession of transmission periods, alternating with idle periods, each of which lasts a number of time slots. Based on this observation, it becomes clear that forcing the SU to sense the channel at the beginning of each time slot is unnecessary and may lead to considerable waste of energy. The main objective of this paper is to investigate new approaches for spectrum sensing by exploring the tradeoffs between energy consumption and secondary network throughput. To this end, we propose a stochastic, energy-aware model to derive the optimal spectrum sensing interval an SU can use to dynamically determine when the next spectrum sensing should be performed. The proposed model allows an SU to adaptively derive the sensing interval based on its required quality of service and current network state, including the PU's network activities and traffic load. Extensive simulation study is performed to assess the effectiveness of our proposed approach in achieving high accuracy with reduced energy consumption. The analysis of the results show that careful tuning of key parameters leads to improved energy efficiency and increased secondary network throughput. [ABSTRACT FROM PUBLISHER]

Cognitive radio networking allows the unlicensed secondary users to opportunistically access the licensed spectrum as long as the performance of the licensed primary users does not degrade. This dynamic spectrum access strategy is enabled by cognitive radio coupled with spectrum sensing technologies. Due to the imperfection of wireless transmissions, collaborative spectrum sensing (CSS) has been proposed to significantly improve the probability of detecting the transmissions of primary users. Nevertheless, current CSS techniques are sensitive to malicious secondary users, leading to a high false alarm rate and low detection accuracy on the presence of the primary users. In this paper, we present several robust collaborative spectrum sensing schemes that can calculate a trust value for each secondary user to reflect its suspicious level and mitigate its harmful effect on cooperative sensing. Our approach explores the spatial and temporal correlations among the reported information of the secondary users to determine the trust values. Extensive simulation study has been performed and our results demonstrate that the proposed schemes can guarantee the accuracy of the cooperative sensing system with a low false alarm rate when a considerable number of secondary users report false information. [ABSTRACT FROM PUBLISHER]

Unbalanced traffic demands of different data center applications are an important issue in designing data center networks (DCN). In this paper, we present our exploratory investigation on a hybrid DCN solution of utilizing wireless transmissions in DCNs. Our work aims to solve the congestion problem caused by a few hot nodes to improve the global performance. We model the wireless transmissions in DCN by considering both the wireless interference and the adaptive transmission rate. Besides, both throughput and job completion time are considered to measure the impact of wireless transmissions on the global performance. Based on the model, we formulate the problem of channel allocation as an optimization problem. We also design an approximation algorithm with an approximation bound of 1/2 and a genetic algorithm to address the scheduling problem. A series of simulations are performed to evaluate and demonstrate the effectiveness of our wireless DCN scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a systematic approach to designing and deploying a RFID Assisted Navigation System (RFID-ANS) for VANETs. RFID-ANS consists of passive tags deployed on roads to provide navigation information while the RFID readers attached to the center of the vehicle bumper query the tag when passing by to obtain the data for navigation guidance. We analyze the design criteria of RFID-ANS and present the design of the RFID reader in detail to support vehicles at high speeds. We also jointly consider the scheduling of the read attempts and the deployment of RFID tags based on the navigation requirements to support seamless navigations. The estimation of the vehicle position and its accuracy are also investigated. [ABSTRACT FROM AUTHOR]