Distributed in-network processing and resource optimization over mobile-health systems

Abstract

Advances in wireless and mobile communication technologies has promoted the development of Mobile-health (m-health) systems to find new ways to acquire, process, transport, and secure the medical data. M-health systems provide the scalability needed to cope with the increasing number of elderly and chronic disease patients requiring constant monitoring. However, the design and operation of such systems with Body Area Sensor Networks (BASNs) is challenging in twofold. First, limited energy, computational and storage resources of the sensor nodes. Second, the need to guarantee application level Quality of Service (QoS). In this paper, we integrate wireless network components, and application-layer characteristics to provide sustainable, energy-efficient and high-quality services for m-health systems. In particular, we propose an Energy-Cost-Distortion (E-C-D) solution, which exploits the benefits of in-network processing and medical data adaptation to optimize the transmission energy consumption and the cost of using network services. Moreover, we present a distributed cross-layer solution, which is suitable for heterogeneous wireless m-health systems with variable network size. Our scheme leverages Lagrangian duality theory to find efficient trade-off among energy consumption, network cost, and vital signs distortion, for delay sensitive transmission of medical data. Simulation results show that the proposed scheme achieves the optimal trade-off between energy efficiency and QoS requirements, while providing 15% savings in the objective function (i.e., E-C-D utility function), compared to solutions based on equal bandwidth allocation.

Distributed Network Image Processing System and Transmission Control Algorithm

“…Rupprecht et al [15] applied a distributed network to network processing and described a distributed connection processing technique that uses delay partitioning to accommodate transient network skew in the cluster. Awad et al [16] proposed an energy cost-distortion solution that integrates wireless network components and application layer features to provide sustainable, energy-efficient, and high-quality services for mobile medical systems. Zhou and Liang [17] used the blockchain credit enhancement system and intelligent contract technology to make light adjustments to the data structure of the distributed ledger for the actual needs of content distribution applications.…”

Decentralization of Services Through Three Tiers in Wireless Body Area Networks

“…To study the effect of sensor communication on the energy consumption and throughput, the authors of [6] proposed two protocols: Optimized Cost Effective and Energy Efficient Routing protocol (OCER), as well as an extended-OCER. In another study [7], a scheme leverages Lagrangian duality theory is designed, to find efficient trade-off among energy consumption, network cost, and vital signs distortion, for delay sensitive transmission of medical data. The optimal trade-off between energy efficiency and QoS requirements, while providing 15% savings the energy-cost-distortion utility function, compared to solutions based on equal bandwidth allocation.…”

Compress or Interfere?

“…However, each objective presents different ranges and units of measurement, hence they need first to be normalized. The goal of the normalization process is to map these objective onto non-dimensional values within the [0,1] range to make them comparable [19]. Therefore, the optimization problem is formulated as follows:…”