353,231 research outputs found

    On cost-effective communication network designing

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    How to efficiently design a communication network is a paramount task for network designing and engineering. It is, however, not a single objective optimization process as perceived by most previous researches, i.e., to maximize its transmission capacity, but a multi-objective optimization process, with lowering its cost to be another important objective. These two objectives are often contradictive in that optimizing one objective may deteriorate the other. After a deep investigation of the impact that network topology, node capability scheme and routing algorithm as well as their interplays have on the two objectives, this letter presents a systematic approach to achieve a cost-effective design by carefully choosing the three designing aspects. Only when routing algorithm and node capability scheme are elegantly chosen can BA-like scale-free networks have the potential of achieving good tradeoff between the two objectives. Random networks, on the other hand, have the built-in character for a cost-effective design, especially when other aspects cannot be determined beforehand.Comment: 6 pages, 4 figure

    Secure and Reconfigurable Network Design for Critical Information Dissemination in the Internet of Battlefield Things (IoBT)

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    The Internet of things (IoT) is revolutionizing the management and control of automated systems leading to a paradigm shift in areas such as smart homes, smart cities, health care, transportation, etc. The IoT technology is also envisioned to play an important role in improving the effectiveness of military operations in battlefields. The interconnection of combat equipment and other battlefield resources for coordinated automated decisions is referred to as the Internet of battlefield things (IoBT). IoBT networks are significantly different from traditional IoT networks due to the battlefield specific challenges such as the absence of communication infrastructure, and the susceptibility of devices to cyber and physical attacks. The combat efficiency and coordinated decision-making in war scenarios depends highly on real-time data collection, which in turn relies on the connectivity of the network and the information dissemination in the presence of adversaries. This work aims to build the theoretical foundations of designing secure and reconfigurable IoBT networks. Leveraging the theories of stochastic geometry and mathematical epidemiology, we develop an integrated framework to study the communication of mission-critical data among different types of network devices and consequently design the network in a cost effective manner.Comment: 8 pages, 9 figure

    IMPLEMENTATION OF VOICE CALL TRANSFER SERVICE BETWEEN SMART PHONE AND TABLET THROUGH WI-FI

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    Communication through voice call leads to significant growth in technology in distant areas where two or more people from opposite ends of world will connect. This research describes a case study of voice call transfer service. This research aims at designing a system that will allow Android users to communicate over Wi-Fi. This design is able to transfer voice of incoming telephone caller over Wi-Fi network at real time through UDP. It uses client/server architecture: Server for receiving telephone call and transferring voice (one user) and client for receiving incoming caller voice and enables communication with server. Architecture designed could be used on Android smart phones with telephony enabled and tablets with telephony not enabled. Outcome of this research will allow users to communicate on real time at no cost. Proposed design gives cost effective, reliable and real time voice communication over Wi-Fi. It provides good and comfort experience to users in emergency situation where user cannot effort cost for telephone call. Proposed design is useful for educational organizations, construction buildings, shopping malls and hospitals which point to new possibilities for voice communication

    Optimal Gateway Placement in Low-cost Smart Cities

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    Rapid urbanization burdens city infrastructure and creates the need for local governments to maximize the usage of resources to serve its citizens. Smart city projects aim to alleviate the urbanization problem by deploying a vast amount of Internet-of-things (IoT) devices to monitor and manage environmental conditions and infrastructure. However, smart city projects can be extremely expensive to deploy and manage partly due to the cost of providing Internet connectivity via 5G or WiFi to IoT devices. This thesis proposes the use of delay tolerant networks (DTNs) as a backbone for smart city communication; enabling developing communities to become smart cities at a fraction of the cost. A model is introduced to aid policy makers in designing and evaluating the expected performance of such networks and results are presented based on a public transit network data-set from Chapel Hill, North Carolina and Louisville, Kentucky. We also demonstrate that the performance of our network can be optimized using algorithms associated on set-cover and Influence maximization problems. Several optimization algorithms are then developed to facilitate the effective placement of gateways within the network model and these algorithms are shown to outperform traditional centrality-based algorithms in terms of cost-efficiency and network performance. Finally, other innovative ways of improving network performance in a low-cost smart city is discussed

    An effective local routing strategy on the BA network

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    In this paper, We propose a effective routing strategy on the basis of the so-called nearest neighbor search strategy by introducing a preferential delivering exponent alpha. we assume that the handling capacity of one vertex is proportional to its degree when the degree is smaller than a cut-off value KK, and is infinite otherwise. It is found that by tuning the parameter alpha, the scale-free network capacity measured by the order parameter is considerably enhanced compared to the normal nearest-neighbor strategy. Traffic dynamics both near and far away from the critical generating rate R_c are discussed. We also investigate R_c as functions of m (connectivity density), K (cutoff value). Due to the low cost of acquiring nearest-neighbor information and the strongly improved network capacity, our strategy may be useful and reasonable for the protocol designing of modern communication networks.Comment: 9 pages, 5 figure

    Matching Theory for Backhaul Management in Small Cell Networks with mmWave Capabilities

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    Designing cost-effective and scalable backhaul solutions is one of the main challenges for emerging wireless small cell networks (SCNs). In this regard, millimeter wave (mmW) communication technologies have recently emerged as an attractive solution to realize the vision of a high-speed and reliable wireless small cell backhaul network (SCBN). In this paper, a novel approach is proposed for managing the spectral resources of a heterogeneous SCBN that can exploit simultaneously mmW and conventional frequency bands via carrier aggregation. In particular, a new SCBN model is proposed in which small cell base stations (SCBSs) equipped with broadband fiber backhaul allocate their frequency resources to SCBSs with wireless backhaul, by using aggregated bands. One unique feature of the studied model is that it jointly accounts for both wireless channel characteristics and economic factors during resource allocation. The problem is then formulated as a one-to-many matching game and a distributed algorithm is proposed to find a stable outcome of the game. The convergence of the algorithm is proven and the properties of the resulting matching are studied. Simulation results show that under the constraints of wireless backhauling, the proposed approach achieves substantial performance gains, reaching up to 30%30 \% compared to a conventional best-effort approach.Comment: In Proc. of the IEEE International Conference on Communications (ICC), Mobile and Wireless Networks Symposium, London, UK, June 201

    Shortest Path versus Multi-Hub Routing in Networks with Uncertain Demand

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    We study a class of robust network design problems motivated by the need to scale core networks to meet increasingly dynamic capacity demands. Past work has focused on designing the network to support all hose matrices (all matrices not exceeding marginal bounds at the nodes). This model may be too conservative if additional information on traffic patterns is available. Another extreme is the fixed demand model, where one designs the network to support peak point-to-point demands. We introduce a capped hose model to explore a broader range of traffic matrices which includes the above two as special cases. It is known that optimal designs for the hose model are always determined by single-hub routing, and for the fixed- demand model are based on shortest-path routing. We shed light on the wider space of capped hose matrices in order to see which traffic models are more shortest path-like as opposed to hub-like. To address the space in between, we use hierarchical multi-hub routing templates, a generalization of hub and tree routing. In particular, we show that by adding peak capacities into the hose model, the single-hub tree-routing template is no longer cost-effective. This initiates the study of a class of robust network design (RND) problems restricted to these templates. Our empirical analysis is based on a heuristic for this new hierarchical RND problem. We also propose that it is possible to define a routing indicator that accounts for the strengths of the marginals and peak demands and use this information to choose the appropriate routing template. We benchmark our approach against other well-known routing templates, using representative carrier networks and a variety of different capped hose traffic demands, parameterized by the relative importance of their marginals as opposed to their point-to-point peak demands
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