Multi-constrained quality-of-service routing (QoSR) is to find a feasible path that satisfies multiple constraints simultaneously, which is a big challenge for mobile ad hoc networks (MANETs) where the topology may change constantly. It has been proved that such a problem is NP-complete. Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem. However, existing solutions, most of which suffered either from excessive computational complexities or from low performance were proposed only for wired networks and cannot be used directly in wireless MANETs. In this paper a novel QoS routing algorithm based on Simulated Annealing (SA_RA) is proposed. This algorithm first uses an energy function to translate multiple QoS weights into a single mixed metric and then seeks to find a feasible path by simulated annealing. The paper outlines simulated annealing algorithm and analyzes the problems met when we apply it to QoSR in MANETs. Theoretical analysis and experiment results demonstrate that the proposed method is an effective approximation algorithms showing better performance than the other pertinent algorithm in seeking the (approximate) optimal configuration within a period of polynomial time.

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Service-oriented online social networks (SOSNs) are emerging ubiquitous platforms for numerous services where service consumers require the selection of trustworthy service providers who are unknown to them before invoking services with the aid of other intermediate participants. Under this circumstance, evaluation of the trust level of the service provider along the social trust paths from the service consumer to the service provider is required. To this end, selection of the optimal social trust path (OSTP) that can yield the most trustworthy evaluation result is a prerequisite. While existing single-trust-value methods can provide good but simple information to service consumers, more trust information, such as social intimacy degree between participants and role impact factor of intermediate participants, should be considered to represent the trust level of a service provider more comprehensively. When more trust information is considered, OSTP selection will become an NP-complete problem. In this paper, we propose path integral Monte Carlo quantum annealing (PIMCQA)-based OSTP (PIMCQA_OSTP) selection algorithm for complex SOSNs. PIMCQA_OSTP serves as the very first quantum inspired OSTP selection algorithm in complex SOSNs. Due to that quantum mechanics work with wave functions that can sample different regions of phase space equally well, and quantum systems can tunnel through classically impenetrable potential barriers between energy valleys, PIMCQA_OSTP shows its outstanding search ability and outperforms existing methods. Results of experiments on a real dataset of online social networks verify that PIMCQA_OSTP is a promising tool and is especially fit for complex SOSNs.Index Terms-Complex service-oriented online social networks, optimal social trust path selection (OSTP), path integral quantum annealing, quantum tunnel, trust level.

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With the rapid growth of commerce and development of Internet technology, a large number of user consumption preferences become available for online market intelligence analysis. A critical demand is to reduce the impact of information overload by using recommendation algorithms. In physical dynamics, network-based recommendation algorithms based on mass-diffusion have been popular for its simplicity and efficiency. In this paper, to solve the problem that most network-based recommendation algorithms cannot distinguish how much the user likes collected items and make resource configuration more reasonable, we propose a novel method called biased network-based inference (BNBI). The proposed method treats rating systems and nonrating systems differently and measures user’s preference for items by means of item similarity. The proposed method is evaluated in real datasets (MovieLens and Last.FM) and compared with some existing classic recommendation algorithms. Experimental results show that the proposed method is more effective and it can reduce the impact of item diversity and discover the real interest of users.

Abstract. Advanced technology in GPS and sensors enables us to track moving objects, such as human beings, animals, vehicles. These mobility data as historical activity data of moving objects, in some degree can reflect some internal and external features of moving objects, how to use the massive high-precision mobile data identify potential and meaningful pattern is the current hot spots and is also a serious problem. Patterns mining also have numerous applications in human mobility understanding, urban planning and ecological studies and a wide variety of other fields. In this paper, we provide a general perspective for studies on the issues of patterns mining by reviewing the methods and algorithms in detail and comparing the existing results on the same issues, providing a quick understanding of research to the worker.

Multi-constrained quality of service (QoS) routing aims at finding an optimal path that satisfies a set of QoS parameters, as an NP complete problem, which is also a big challenge for wireless mesh networks (WMNs). Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem. However, existing solutions, most of which suffered either from excessive computational complexities or from low performance, were proposed only for wired networks and cannot be used directly in wireless mesh networks. In this paper, we propose a novel routing scheme based on mean field annealing (MFA-RS) to solve this problem. MFA-RS first uses a function of two QoS parameters, wireless link's delay and transmission success rate as the cost function, and then seeks to find a feasible path by MFA. Because MFA-RS uses a set of deterministic equations to replace the stochastic process in simulated annealing (SA) and uses saddle point approximation in the calculation of the stationary probability distribution at equilibrium, the convergence time is much less than the routing scheme based on SA (SA-RS). Simulation results demonstrate that MFA-RS is an effective algorithm and is very fit for WMNs.