In this paper a reliable, efficient in terms of power consumption and high stable network is proposed for Wireless Body Area Sensor Networks. Eight sensor nodes are used from which two are recording critical data. These two sensors are not apart of multi-hopping but send data direct to the sink. Remaining six sensors are computed to become a forwarder node. Forwarder nodes gathers data from sensors and after aggregating sends ti the sink. Two parameters are set for cost function so that a forwarder node is selected. If a sensor is having minimum distance and maximum energy as compared to the entire nodes then it will be selected as forwarder node. Multi-hopping is used to reduce the distance of data communication and to save energy consumption. Simulation is carried out and shows stable results.

An Energy Efficient Routing Protocol for Wireless Body Area Sensor Networks

Routing is one of the important topics in wireless sensor networks (WSNs), and has been attracting the research community in the last decade. Routing based on ant colony optimization (ACO) is a type of transmission method rich in characteristics. There are several survey papers that present and compare routing protocols from various perspectives, but the survey on ACO-based routing is still missing. This paper makes a first attempt to provide a comprehensive review on ACO-based routing protocols in WSNs. First, we offer a classification of these routing algorithms. Second, the most representative ACO-based routing protocols are described, discussed, and qualitatively compared. Finally, we put forward some open issues concerning the design of WSNs. This survey aims to provide useful guidance for system designers on how to evaluate and select appropriate routing schemes for specific applications.

Routing Protocols Based on Ant Colony Optimization in Wireless Sensor Networks: A Survey

Game theory is a field of applied mathematics that studies strategic behavior of rational factors. In other words, game theory is a collection of analytical tools that can be used to make optimal choices in interactional and decision making problems. Optimization in mathematics and computer science is the choice of the best member of an existing collection for a specific purpose. Several optimization methods have been used in many problems to minimize costs or maximize profits. From a particular point of view, it can be said that the game theory is in fact a kind of optimization. In this paper, a combined use of game theory and optimization algorithms has been reviewed and a new categorization is presented for researches which have been conducted in this area. In some of these combinations, game theory has been used to improve the performance of optimization algorithms, and in some others, optimizations methods help to solve game theory problems. Game theory and optimization algorithms are also used together to solve some other problems.

A Survey on the Combined Use of Optimization Methods and Game Theory

With the coming of the fifth-generation (5G) mobile communications, in mobile edge computing (MEC), the growth of user services and the personalization of QoS requirements have posed great challenges for heterogeneous wireless networks (HWNs) access selection. Based on the multiattribute decision theory and the fuzzy logic theory, we propose a novel network selection scheme for multiservice QoS requirements in MEC. The main procedures of the scheme include dynamic adaptive process, fuzzy process, hierarchical analysis, and integrated attributes assessment. The scheme proposed contributes to efficiently reduce the ping-pong effect and effectively select accurate network in a dynamic environment. Simulation results show that our scheme can select network access according to the type of user services and whether to switch networks. In addition, compared with commonly used simple additive weighting (SAW), random access selection (RAS), and price-based and QoS-based network selection scheme, our scheme has better performance in improving average user satisfaction and reducing access failures.

Adaptive Multiservice Heterogeneous Network Selection Scheme in Mobile Edge Computing

The intelligent use of resources enabled by Internet of Things has raised the expectations of the technical as well as the consumer community. However there are many challenges in designing an IoT healthcare system, like security, authentication and exchanging data. The IoT healthcare system, is transforming everyday physical objects, medical devices that surround us into an embedded smart healthcare system. Public healthcare has been paid an increasing attention given the human population and medical expenses exponential growth. It is well known that an effective monitoring healthcare system can detect abnormalities of health conditions in time and make diagnoses according to sensing (WBSN) data. This paper propose a general architecture of a smart mobile IoT healthcare system for monitoring patients risk using a smart phone and 5G. The design of multi-protocol unit for universal connectivity. Web and mobile applications developed to meet the needs of patients, doctors, laboratories analysis and hospitals services. The system advises and alerts in real time the doctors/medical assistants about the changing of vital parameters of the patients, such as body temperature, pulse and Oxygen in Blood etc… and also about important changes on environmental parameters, in order to take preventive measures, save lives in critical care and emergency situations.

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Smart Mobile Healthcare System based on WBSN and 5G

Balancing emergency message dissemination and network lifetime in wireless body area network using ant colony optimization and Bayesian game formulation

In this paper, heart disease prediction modeled using partially observable markov decision process (POMDP) is proposed. In emergency, the patient is alerted through the doctor by fog computing. Ambulance sent to the location of patient at critical situations. The doctor gets the data through fog computing iFogSim. Fog computing in healthcare is a new area, which gains more attraction in research community. Many researches focus on cardiovascular disease i.e. heart disease. The important risk factor for cardiovascular disease is increase in blood viscosity. The highly viscous nature of blood does not allow the blood to flow creating a resistance in the blood flow. Heart disease risk factors are high blood pressure, obesity, diabetes, increased blood viscosity, etc. With the help of POMDP’s states, observations, beliefs, probability transitions the patient health is noted. The POMDP model for heart disease prediction computes the policy approximation using states and timeslots. Rewards are tabulated using policy approximations over different iterations.

Blood Viscosity based Heart Disease Risk Prediction Model in Edge/Fog Computing

This paper is a collection of telemedicine techniques used by wireless body area networks (WBANs) for emergency conditions. Furthermore, Bayes’ theorem is proposed for predicting emergency conditions. With prior knowledge, the posterior probability can be found along with the observed evidence. The probability of sending emergency messages can be determined using Bayes’ theorem with the likelihood evidence. It can be viewed as medical decision-making, since diagnosis conditions such as emergency monitoring, delay-sensitive monitoring, and general monitoring are analyzed with its network characteristics, including data rate, cost, packet loss rate, latency, and jitter. This paper explains the network model with 16 variables, with one describing immediate consultation, as well as another three describing emergency monitoring, delay-sensitive monitoring, and general monitoring. The remaining 12 variables are observations related to latency, cost, packet loss rate, data rate, and jitter.

https://www.mdpi.com/1424-8220/20/7/2153/pdf

Wireless Body Area Network (WBAN)-Based Telemedicine for Emergency Care.

Multi Criteria Decision Making (MCDM) is useful for choosing a possible objective. The objective is to investigate how far TOPSIS method of MCDM can be utilized for delay sensitive network selection problem. In this paper, TOPSIS method is used for taking decision in delay sensitive network selection for achieving reliability of network selection with Wireless Body Area Network (WBAN) parameters; viz. end-to-end-delay, network lifetime and throughput. The best solution for selecting a network model is ranked using this method. MCDM uses infinite number of alternatives for analysis. TOPSIS compares the attributes of each alternative, normalizes each attribute and also calculates the distance of each alternative from the ideal solution.

Topsis based delay sensitive network selection for wireless body area networks

Background Network lifetime is an essential performance metric for medical body area networks (MBAN) since nodes meant to monitor medical parameters continuously for a longer amount of time. This paper focuses on various schemes for enhancing the network lifetime through an analytical approach. Methods An analytical model for enhanced lifetime of sensor nodes is proposed. The proposed model consists of both relay nodes (RN) and sensor nodes (SN) towards enhancing the longevity of network lifetime. The routing protocol is designed to collect the sensed information from SN by adapting optimal path towards gateway. The optimal distance between SN and RN is chosen based on best quality link which ensures the packet delivery. The total installation cost of RN, the total energy consumption of both RN and SN, the traffic serviced from all sensors and data routing to nodes are the constraints considered in the proposed framework for achieving the optimal path though efficient relaying. Results The proposed multi-tier telemedicine system is extensively simulated for describing the optimal network path for MBAN-based e-health services. The proposed work is modelled using integer linear programming that optimizes the location and number of relays. Relays are deployed for minimizing the cost of network installation of RN. The energy which is consumed by both sensors and relays is minimized while ensuring full coverage with effective routing of e-health services. The network longevity is analyzed during both normal and emergency scenarios.

R. Latha

Papers

Balancing emergency message dissemination and network lifetime in wireless body area network using ant colony optimization and Bayesian game formulation

Blood Viscosity based Heart Disease Risk Prediction Model in Edge/Fog Computing

Wireless Body Area Network (WBAN)-Based Telemedicine for Emergency Care.

Topsis based delay sensitive network selection for wireless body area networks

Efficient Relaying for Enhanced Network Longevity for E-health IOT Services in Medical Body Area Networks