Voxel selection in fMRI data analysis based on sparse representation

Multivariate pattern analysis approaches toward detection of brain regions from fMRI data have been gaining attention recently. In this study, we introduce an iterative sparse-representation-based algorithm for detection of voxels in functional MRI (fMRI) data with task relevant information. In each iteration of the algorithm, a linear programming problem is solved and a sparse weight vector is subsequently obtained. The final weight vector is the mean of those obtained in all iterations. The characteristics of our algorithm are as follows: 1) the weight vector (output) is sparse; 2) the magnitude of each entry of the weight vector represents the significance of its corresponding variable or feature in a classification or regression problem; and 3) due to the convergence of this algorithm, a stable weight vector is obtained. To demonstrate the validity of our algorithm and illustrate its application, we apply the algorithm to the Pittsburgh Brain Activity Interpretation Competition 2007 functional fMRI dataset for selecting the voxels, which are the most relevant to the tasks of the subjects. Based on this dataset, the aforementioned characteristics of our algorithm are analyzed, and a comparison between our method with the univariate general-linear-model-based statistical parametric mapping is performed. Using our method, a combination of voxels are selected based on the principle of effective/sparse representation of a task. Data analysis results in this paper show that this combination of voxels is suitable for decoding tasks and demonstrate the effectiveness of our method

Background Traffic-Based Retransmission Algorithm for Multimedia Streaming Transfer over Concurrent Multipaths

The content-rich multimedia streaming will be the most attractive services in the next-generation networks. With function of distribute data across multipath end-to-end paths based on SCTP's multihoming feature, concurrent multipath transfer SCTP (CMT-SCTP) has been regarded as the most promising technology for the efficient multimedia streaming transmission. However, the current researches on CMT-SCTP mainly focus on the algorithms related to the data delivery performance while they seldom consider the background traffic factors. Actually, background traffic of realistic network environments has an important impact on the performance of CMT-SCTP. In this paper, we firstly investigate the effect of background traffic on the performance of CMT-SCTP based on a close realistic simulation topology with reasonable background traffic in NS2, and then based on the localness nature of background flow, a further improved retransmission algorithm, named RTX_CSI, is proposed to reach more benefits in terms of average throughput and achieve high users' experience of quality for multimedia streaming services

Extension of MIH for FPMIPv6 (EMIH-FPMIPv6) to support optimized heterogeneous handover

Fast handover for Proxy Mobile IPv6 (FPMIPv6) can optimize the handover performance compared with PMIPv6 in terms of handover delay and packet loss. However, FPMIPv6 cannot handle heterogeneous handovers due to the lack of unified Layer 2 triggering mechanism. While Media Independent Handover (MIH) can provide heterogeneous handover support, and a lot of MIH-based integration solutions have been proposed. However, most of these solutions are based on the integration of MIH and PMIPv6, and require additional mechanisms such as L2 scanning, handover coordinator or neighbor discovery, which are out of the scope of MIH and difficult to be standardized. Furthermore, the direct integration of MIH and FPMIPv6 will cause redundant signaling cost due to the similar functions such as MIH handover commit procedure in MIH and inter-MAG (Mobility Access Gateway) tunnel setup in FPMIPv6. This paper provides a comprehensive survey on these solutions and compares each solution's functionality and characteristic, and then proposes an integration scheme based on Extension of MIH for FPMIPv6 (EMIH-FPMIPv6) to support optimized heterogeneous handover, which extends the existing MIH standard and reduces the redundant messages interaction caused by FPMIPv6 and MIH. This paper adopts the city section mobility model and heterogeneous networks model to analyze and compare the performance of EMIH-FPMIPv6 under different heterogeneous handover scenarios. The analytical results show that EMIH-FPMIPv6 is capable of reducing the handover delay and the signaling cost compared to the solution specified in MIH standard (noted as standard handover solution) and FPMIPv6. © 201

Peering Strategic Game Models for Interdependent ISPs in Content Centric Internet

Emergent content-oriented networks prompt Internet service providers (ISPs) to evolve and take major responsibility for content delivery. Numerous content items and varying content popularities motivate interdependence between peering ISPs to elaborate their content caching and sharing strategies. In this paper, we propose the concept of peering for content exchange between interdependent ISPs in content centric Internet to minimize content delivery cost by a proper peering strategy. We model four peering strategic games to formulate four types of peering relationships between ISPs who are characterized by varying degrees of cooperative willingness from egoism to altruism and interconnected as profit-individuals or profit-coalition. Simulation results show the price of anarchy (PoA) and communication cost in the four games to validate that ISPs should decide their peering strategies by balancing intradomain content demand and interdomain peering relations for an optimal cost of content delivery

Information Exchange rather than Topology Awareness: Cooperation between P2P Overlay and Traffic Engineering

Solutions to the routing strategic conflict between noncooperative P2P overlay and ISP underlay go separate ways: hyperselfishness and cooperation. Unpredictable (possibly adverse) impact of the hyperselfish topology awareness, which is adopted in both overlay routing and traffic engineering, has not been sufficiently studied in the literature. Topology-related information exchange in a cooperatively efficient way should be highlighted to alleviate the cross-layer conflict. In this paper, we first illustrate the hyperselfish weakness with two dynamic noncooperative game models in which hyperselfish overlay or underlay has to accept a suboptimal profit. Then we build a synergistic cost-saving (SC) game model to reduce the negative effects of noncooperation. In the SC model, through information exchange, that is, the classified path-delay metrics for P2P overlay and peer locations for underlay, P2P overlay selects proximity as well as saving traffic transit cost for underlay, and ISP underlay adjusts routing to optimize network cost as well as indicating short delay paths for P2P. Simulations based on the real and generated topologies validate cost improvement by SC model and find a proper remote threshold value to limit P2P traffic from remote area, cross-AS, or cross-ISP