MAR : message-aware routing for opportunistic wireless ad hoc networks

In this paper we study the problem of routing in opportunistic wireless network, and propose a novel routing mechanism, message-aware routing (MAR). Using MAR, the messages can be prioritized at mobile nodes and the resources will be allocated accordingly. The MAR uses the message-aware socializing model to classify mobile nodes into different social groups. In MAR, nodes only maintain up-to-date routing information for the nodes in the same social group and the messages for the nodes in the same social group will have higher priority to be delivered. The MAR improves the routing efficiency in terms of reduced traffic and a higher delivery success rate. Further, MAR is constructed in decentralized way and does not require any centralized infrastructure. Experiments using NS2 simulator show that the MAR achieves higher delivery rate than the Epidemic and Prophet routing.

GeoConnect : geographic and connectivity-aware routing protocol for wireless sensor network

Sensor nodes are closely tied with their geographic location and their connectivity. In recent years many routing protocols have been developed to provide efficient strategy. But most of them are either focus on the geographic proximity or on connectivity. However in sparse network, Geographic routing would fail at local dead ends where a node has no neighbour closer to destination. In contrast, connectivity-based routing may result in non-optimal path and overhead management. In this paper we designed a scalable and distributed routing protocol, GeoConnect, which considers geographic proximity and connectivity for choosing next hop. In GeoConnecl, we construct a new naming system that integrates geographic and connectivity information into a node identification. We use dissimilarity function to compute the dissimilarity and apply a distributed routing algorithm to route packets. The experimental results show that GeoConnect routing provides robust and better performance than sole geographic routing or connectivity routing.

S-Kcore : a social-aware Kcore decomposition algorithm in pocket switched networks

The key nodes in network play the critical role in system recovery and survival. Many traditional key nodes selection algorithms utilize the characters of the physical topology to find the key nodes. But they can hardly succeed in the mobile ad hoc network due to the mobility nature of the network. In this paper we propose a social-aware Kcore selection algorithm to work in the Pocket Switched Network. The social view of the network suggests the social position of the mobile nodes can help to find the key nodes in the Pocket Switched Network. The S-Kcore selection algorithm is designed to exploit the nodes' social features to improve the performance in data communication. Experiments use the NS2 shows S-Kcore selection algorithm workable in the Pocket Switched Network. Furthermore, with the social behavior information, those key nodes are more suitable to represent and improve the whole network's performance.

M-Dimension : multi-characteristics based routing protocol in human associated delay-tolerant networks with improved performance over one dimensional classic models

Human associated delay-tolerant network (HDTN) is a new delay-tolerant network where mobile devices are associated with humans. It can be viewed from both their geographic and social dimensions. The combination of these different dimensions can enable us to more accurately comprehend a delay-tolerant network and consequently use this multi-dimensional information to improve overall network efficiency. Alongside the geographic dimension of the network which is concerned with geographic topology of routing, social dimensions such as social hierarchy can be used to guide the routing message to improve not only the routing efficiency for individual nodes, but also efficiency for the entire network.

We propose a multi-dimensional routing protocol (M-Dimension) for the human associated delay-tolerant network which uses the local information derived from multiple dimensions to identify a mobile node more accurately. Each dimension has a weight factor and is organized by the Distance Function to select an intermediary and applies multi-cast routing. We compare M-Dimension to existing benchmark routing protocols using the MIT Reality Dataset, a well-known benchmark dataset based on a human associated mobile network trace file. The results of our simulations show that M-Dimension has a significant increase in the average success ratio and is very competitive when End-to-End Delay of packet delivery is used in comparison to other multi-cast DTN routing protocols.

Feel bored? Join Verse! Engineering Vehicular Proximity Social Network

Travellers in vehicles often have strong willingness to share their travel experience and exchange information to each other through social networks2, such as Facebook and Twitter. This, however, can be costly due to the limited connections to Internet on the road. In this paper we develop Verse to facilitate the social communications among vehicle travellers on highways. Verse enables passengers on-board vehicles to share the content information, such as travel blogs with pictures, among each other using the impromptu wireless inter-vehicle communications. Unlike traditional online social networks, which are built upon the reliable IP networks, vehicular social networks face fundamental challenges in that: 1) users are anonymous and strangers to each other and hard to identify potential friends of shared interests, and 2) users communicate through intermittent and unreliable inter-vehicle connections. On addressing the two challenges, Verse implements a friend recommendation function, which helps passengers efficiently identify potential social friends with both shared interests and relatively reliable wireless connections. In addition, Verse is equipped with a social-aware rate control scheme towards efficient utilization of network bandwidth. Using extensive simulations, we show that the friend recommendation function of Verse can effectively predict the mobility of vehicles to assist the social communication, and the social-aware rate control scheme quickly and efficiently adapts the vehicle’s transmission rate according to their social impacts.

Dominating set and network coding-based routing in wireless mesh networks

Wireless mesh networks are widely applied in many fields such as industrial controlling, environmental monitoring, and military operations. Network coding is promising technology that can improve the performance of wireless mesh networks. In particular, network coding is suitable for wireless mesh networks as the fixed backbone of wireless mesh is usually unlimited energy. However, coding collision is a severe problem affecting network performance. To avoid this, routing should be effectively designed with an optimum combination of coding opportunity and coding validity. In this paper, we propose a Connected Dominating Set (CDS)-based and Flow-oriented Coding-aware Routing (CFCR) mechanism to actively increase potential coding opportunities. Our work provides two major contributions. First, it effectively deals with the coding collision problem of flows by introducing the information conformation process, which effectively decreases the failure rate of decoding. Secondly, our routing process considers the benefit of CDS and flow coding simultaneously. Through formalized analysis of the routing parameters, CFCR can choose optimized routing with reliable transmission and small cost. Our evaluation shows CFCR has a lower packet loss ratio and higher throughput than existing methods, such as Adaptive Control of Packet Overhead in XOR Network Coding (ACPO), or Distributed Coding-Aware Routing (DCAR).

Service-oriented wireless sensor networks and an energy-aware mesh routing algorithm

Service-oriented wireless sensor networks (WSNs) are being paid more and more attention because service computing can hide complexity of WSNs and enables simple and transparent access to individual sensor nodes. Existing WSNs mainly use IEEE 802.15.4 as their communication specification, however, this protocol suite cannot support IP-based routing and service-oriented access because it only specifies a set of physical- and MAC-layer protocols. For inosculating WSNs with IP networks, IEEE proposed a 6LoWPAN (IPv6 over LoW Power wireless Area Networks) as the adaptation layer between IP and MAC layers. However, it is still a challenging task how to discover and manage sensor resources, guarantee the security of WSNs and route messages over resource-restricted sensor nodes. This paper is set to address such three key issues. Firstly, we propose a service-oriented WSN architectural model based on 6LoWPAN and design a lightweight service middleware SOWAM (service-oriented WSN architecture middleware), where each sensor node provides a collection of services and is managed by our SOWAM. Secondly, we develop a security mechanism for the authentication and secure connection among users and sensor nodes. Finally, we propose an energyaware mesh routing protocol (EAMR) for message transmission in a WSN with multiple mobile sinks, aiming at prolonging the lifetime of WSNs as long as possible. In our EAMR, sensor nodes with the residual energy lower than a threshold do not forward messages for other nodes until the threshold is leveled down. As a result, the energy consumption is evened over sensor nodes significantly. The experimental results demonstrate the feasibility of our service-oriented approach and lightweight middleware SOWAM, as well as the effectiveness of our routing algorithm EAMR.

A sentiment-aware approach to community formation in social media

Participating in a community exemplifies the aspect of sharing, networking and interacting in a social media system. There has been extensive work on characterising on-line communities by their contents and tags using topic modelling tools. However, the role of sentiment and mood has not been studied. Arguably, mood is an integral feature of a text, and becomes more significant in the context of social media: two communities might discuss precisely the same topics, yet within an entirely different atmosphere. Such sentiment-related distinctions are important for many kinds of analysis and applications, such as community recommendation. We present a novel approach to identification of latent hyper-groups in social communities based on users’ sentiment. The results show that a sentiment-based approach can yield useful insights into community formation and metacommunities, having potential applications in, for example, mental health—by targeting support or surveillance to communities with negative mood—or in marketing—by targeting customer communities having the same sentiment on similar topics.

Utility-aware social network graph anonymization

As the need for social network data publishing continues to increase, how to preserve the privacy of the social network data before publishing is becoming an important and challenging issue. A common approach to address this issue is through anonymization of the social network structure. The problem with altering the structure of the links relationship in social network data is how to balance between the gain of privacy and the loss of information (data utility). In this paper, we address this problem. We propose a utility-aware social network graph anonymization. The approach is based on a new metric that calculates the utility impact of social network link modification. The metric utilizes the shortest path length and the neighborhood overlap as the utility value. The value is then used as a weight factor in preserving structural integrity in the social network graph anonymization. For any modification made to the social network links, the proposed approach guarantees that the distance between vertices in the modified social network stays as close as the original social network graph prior to the modification. Experimental evaluation shows that the proposed metric improves the utility preservation as compared to the number-of-change metric.