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Smart meters (SMs) measure and transmit fine-grained electricity consumption data to the data center at a certain high frequency (such as every 15 minutes). A data aggregation point (DAP) is a relay device between a cluster of SMs and data centers. The placement of DAPs significantly impacts the cost-effectiveness and quality of service (QoS) of the communication system. Nowadays, many newly installed SMs not only can send data to the DAPs but also receive/send data from/to other SMs. This paper proposes a novel approach for the optimal DAP placement in a multi-hop routing scenario, where SMs can serve as small relay devices so that communications among SMs can be leveraged to reduce the overall communication cost. To do so, we formulate a mixed-integer optimization problem that minimizes three types of cost: installation, transmission, and delay cost. Since the optimization problem involves too many binary variables to be efficiently solved to optimality, a heuristic approach is developed to obtain a desirable solution with a low computational burden. The heuristic iteratively implements clustering approximation, pole assignment, and optimal routing until convergence of the total cost value. Both an illustrative example and case studies verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this letter, we propose a new backpressure-based optimal joint routing and congestion control scheme for wireless multihop networks operating solely on energy harvesting. Compared to previous works, we assume: i) different energy consumption for each commodity, and ii) energy is consumed when a node transmits, receives and produces traffic. We show that this requires infinite battery capacity for logarithmic utility functions and further improve the battery capacity computation. Finally, we show queue stability, while ensuring energy causality. [ABSTRACT FROM AUTHOR]

In this paper, we formulate a network utility maximization (NUM) problem, targeting an optimal cross-layer network operation, while considering time-varying and random possibly non-stationary wireless channels. As indicated in the literature, this problem imposes scalability constraints when the time horizon of the network control increases, impeding an online (i.e., real-time) application of its solution during the network operation. To achieve an online network control, in this paper, we leverage on model predictive control (MPC) or receding horizon control (RHC) for the solution of the NUM problem. Furthermore, MPC/RHC allows for the adaptation of the optimal controls in dynamic and evolving network conditions, in our case with respect to the wireless channels, the modeling parameters of which are estimated in an online fashion. We present and analyze the NUM problem, while we appropriately reformulate it for applying MPC/RHC. Then, we describe the MPC/RHC-based algorithmic solution, which determines the decisions for the online network control including power control, scheduling, routing, and congestion control, while we discuss stability and optimality issues. Finally, we evaluate the proposed methodology via numerical results and we show that the performance lies very close to the optimal one even for relatively small receding horizon lengths that significantly reduce the computational time complexity. [ABSTRACT FROM PUBLISHER]

In this paper, we study, analyze, and evaluate a performance-aware cross-layer design approach for wireless multihop networks. Through network utility maximization (NUM) and weighted network graph modeling, a cross-layer algorithm for performing jointly routing, scheduling, and congestion control is introduced. The performance awareness is achieved by both the appropriate definition of the link weights for the corresponding application's requirements and the introduction of a weighted backpressure (BP) routing/scheduling. Contrary to the conventional BP, the proposed algorithm scales the congestion gradients with the appropriately defined per-pair (link, destination) weights. We analytically prove the queue stability achieved by the proposed cross-layer scheme, while its convergence to a close neighborhood of the optimal source rates' values is proven via an \varepsilon-subgradient approach. The issue of the weights' assignment based on various quality-of-service (QoS) metrics is also investigated. Through modeling and simulation, we demonstrate the performance improvements that can be achieved by the proposed approach—when compared against existing methodologies in the literature—for two different examples with diverse application requirements, emphasizing respectively on delay and trustworthiness. [ABSTRACT FROM AUTHOR]

Network utility maximization is often applied for the cross-layer design of wireless networks considering known wireless channels. However, realistic wireless channel capacities are stochastic bearing time-varying statistics, necessitating the redesign and solution of NUM problems to capture such effects. Based on NUM theory we develop a framework for scheduling, routing, congestion control and power control in wireless multihop networks that considers stochastic long or short term fading wireless channels. Specifically, the wireless channel is modeled via stochastic differential equations alleviating several assumptions that exist in state-of-the-art channel modeling within the NUM framework such as the finite number of states or the stationarity. Our consideration of wireless channel modeling leads to a NUM problem formulation that accommodates non-convex and time-varying utilities. We consider both cases of non orthogonal and orthogonal access of users to the medium. In the first case, scheduling is performed via power control, while the latter separates scheduling and power control and the role of power control is to further increase users' optimal utility by exploiting random reductions of the stochastic channel power loss while also considering energy efficiency. Finally, numerical results evaluate the performance and operation of the proposed approach and study the impact of several involved parameters on convergence. [ABSTRACT FROM PUBLISHER]

Mobile social networks have the lion's share in modern mobile telecommunications, and their interaction with the underlying infrastructure networks has attracted significant attention due to its impact on resource management. In this article, we present and demonstrate a framework for addressing such interplay between online social networks and wireless communications by exploiting principles from the theory of utility-based engineering and elements from social network analysis. We aim at a holistic design framework that allows the joint development of improved resource management mechanisms for future mobile wireless infrastructures and their social counterparts. We demonstrate the proposed methodology and reveal the key aspects of designing and exploiting convenient utility functions within the framework of network science in order to better manage the available resources, improve infrastructures, and eventually obtain from them the maximum possible benefit. We establish the above principles and emerging design potentials in future complex networks by presenting two tangible examples where personalized advertising and topology control in MSNs are used to exploit and validate different network and individual socio-utility maximization features, respectively. [ABSTRACT FROM PUBLISHER]

Contemporary traffic demands call for efficient infrastructures capable of sustaining increasing volumes of social communications. In this work, we focus on improving the properties of wireless multihop networks with social features through network evolution. Specifically, we introduce a framework, based on inverse Topology Control (iTC), for distributively modifying the transmission radius of selected nodes, according to social paradigms. Distributed iTC mechanisms are proposed for exploiting evolutionary network churn in the form of edge/node modifications, without significantly impacting available resources. We employ continuum theory for analytically describing the proposed top-down approach of infusing social features in physical topologies. Through simulations, we demonstrate how these mechanisms achieve their goal of reducing the average path length, so as to make a wireless multihop network scale like a social one, while retaining its original multihop character. We study the impact of the proposed topology modifications on the operation and performance of the network with respect to the average throughput, delay, and energy consumption of the induced network. [ABSTRACT FROM AUTHOR]