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Here, when a data packet is broadcast by an upstream node and has happened to be received by a downstream node further along the route, it continues its way from there and thus will arrive at the destination node sooner. This is achieved through cooperative data communication at the link and network layers. This work is a powerful extension to the pioneering work of ExOR. We test CORMAN and compare it to AODV, and observe significant performance improvement in varying mobile settings.Index Terms-Cooperative communication, opportunistic routing, opportunistic forwarding, mobile ad hoc networks, proactive source routing, local retransmission, forwarder list update

To study the influence of information on the behavior of stock markets, a common strategy in previous studies has been to concatenate the features of various information sources into one compound feature vector, a procedure that makes it more difficult to distinguish the effects of different information sources. We maintain that capturing the intrinsic relations among multiple information sources is important for predicting stock trends. The challenge lies in modeling the complex space of various sources and types of information and studying the effects of this information on stock market behavior. For this purpose, we introduce a tensor-based information framework to predict stock movements. Specifically, our framework models the complex investor information environment with tensors. A global dimensionality-reduction algorithm is used to capture the links among various information sources in a tensor, and a sequence of tensors is used to represent information gathered over time. Finally, a tensor-based predictive model to forecast stock movements, which is in essence a high-order tensor regression learning problem, is presented. Experiments performed on an entire year of data for China Securities Index stocks demonstrate that a trading system based on our framework outperforms the classic Top- N trading strategy and two state-of-the-art media-aware trading algorithms.

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The non-linear interaction effect among multiple genetic factors, i.e. epistasis, has been recognized as a key component in understanding the underlying genetic basis of complex human diseases and phenotypic traits. Due to the statistical and computational complexity, most epistasis studies are limited to interactions with an order of two. We developed ViSEN to analyze and visualize epistatic interactions of both two-way and three-way. ViSEN not only identifies strong interactions among pairs or trios of genetic attributes, but also provides a global interaction map that shows neighborhood and clustering structures. This visualized information could be very helpful to infer the underlying genetic architecture of complex diseases and to generate plausible hypotheses for further biological validations. ViSEN is implemented in Java and freely available at https://sourceforge.net/projects/visen/.

Abstract-Opportunistic data forwarding has drawn much attention in the research community of multihop wireless networking, with most research conducted for stationary wireless networks. One of the reasons why opportunistic data forwarding has not been widely utilized in mobile ad hoc networks (MANETs) is the lack of an efficient lightweight proactive routing scheme with strong source routing capability. In this paper, we propose a lightweight proactive source routing (PSR) protocol. PSR can maintain more network topology information than distance vector (DV) routing to facilitate source routing, although it has much smaller overhead than traditional DV-based protocols [e.g., destination-sequenced DV (DSDV)], link state (LS)-based routing [e.g., optimized link state routing (OLSR)], and reactive source routing [e.g., dynamic source routing (DSR)]. Our tests using computer simulation in Network Simulator 2 (ns-2) indicate that the overhead in PSR is only a fraction of the overhead of these baseline protocols, and PSR yields similar or better data transportation performance than these baseline protocols.Index Terms-Differential update, mobile ad hoc networks (MANETs), opportunistic data forwarding, proactive routing, routing overhead control, source routing, tree-based routing.

Position information is an important aspect of a mobile device's context. While GPS is widely used to provide location information, it does not work well indoors. Wi-Fi network infrastructure is found in many public facilities and can be used for indoor positioning. In addition, the ubiquity of Wi-Fi-capable devices makes this approach especially cost-effective. In recent years, "folksonomy"-like systems such as Wikipedia or Delicious Social Bookmarking have achieved huge successes. User collaboration is the defining characteristic of such systems. For indoor positioning mechanisms, it is also possible to incorporate collaboration in order to improve system performance, especially for fingerprinting-based approaches. In this article, a robust and efficient model is devised for integrating human-centric collaborative feedback within a baseline Wi-Fi fingerprinting-based indoor positioning system. Experiments show that the baseline system performance (i.e., positioning error and precision) is improved by collecting both positive and negative feedback from users. Moreover, the feedback model is robust with respect to malicious feedback, quickly self-correcting based on subsequent helpful feedback from users.

Network coding and opportunistic routing are two recognized innovative ideas to improve the performance of wireless networks by utilizing the broadcast nature of the wireless medium. In the last decade, there has been considerable research on how to synergize inter-flow network coding and opportunistic routing in a single joint protocol outperforming each in any scenario. This paper explains the motivation behind the integration of these two techniques, and highlights certain scenarios in which the joint approach may even degrade the performance, emphasizing the fact that their synergistic effect cannot be accomplished with a naive and perfunctory combination. This survey paper also provides a comprehensive taxonomy of the joint protocols in terms of their fundamental components and associated challenges, and compares existing joint protocols. We also present concluding remarks along with an outline of future research directions.Inter-flow network coding, opportunistic routing, network coding-aware routing, unicast traffic, multi-hop wireless mesh networks. I. INTRODUCTIONWireless mesh network (WMN) [1], [2] is a type of wireless communication networks aiming to realize the dream of a seamlessly connected world. In mesh infrastructure, radio nodes are connected via wireless links creating a multi-hop wireless network, and nodes can talk to each other and pass data over long distances. This is realized by forming long paths consisting of smaller segments and handing off data over mulitple hops. This cooperative data delivery is the key idea of mesh networks to share connectivity across a large area with inexpensive wireless technologies.Despite these advancements, users' expectations rise fast, and new applications require higher throughput and lower delay [3]. In addition, the performance of wireless networks is significantly restricted by interference, and the unreliability of the wireless channel. Also, it is adversely affected by the contention among different data flows and devices in sharing bandwidth and other network resources. However, since the last decade two promising approaches of "Opportunistic Routing" and "Network Coding" are proved to improve the performance of wireless networks significantly by creatively utilizing the broadcast nature of the wireless medium.Network coding (NC), more specifically inter-flow network coding (IXNC), is the process of forwarding more than one packet in each transmission. Doing so, it increases the "effective" capacity of the network [4] and improves the throughput. Opportunistic routing 1 (OR) also benefits from the broadcast nature of wireless networks via path diversity. In OR, in contrast to traditional forwarding, there is no fixed route, and nodes do not forward a packet to a specified pre-selected next-hop. In fact, a node first broadcasts the packet, and then the next-hop is selected among all neighbors that have received the packet successfully. In addition, as explained in Section II-B, OR can reduce the total number of transmissions by exploiting long but p...