1. Introduction

The health care applications, related to wireless sensor networks, focus on the improvement of medical facilities especially for elderly people living at home. The design constraints, related to pervasive health care systems in body area network devices, includes radiofrequency identifier tags, electrocardiogram sensors, and accelerometers that are worn by individuals. Different protocols and standards had been designed for health care systems including IEEE 802.15.4 and IEEE 802.15.6 for Zigbee and WBAN health care standard. In pervasive health care systems, different medical applications had been designed for remote patient monitoring [1]. These most common applications used nowadays includes Mobi Health, Code Blue, Alarm Net, Life Guard, Med. Supervision, WLAN ECG, Mobile ECG, and AWARENESS [2, 3]. A patient alarm monitoring system is typically designed for elderly people living at home in case of critical emergency circumstances. The WBAN applications are responsible for monitoring health care of patients by using lightweight sensors mounted on the human body. The lightweight sensor devices are used in monitoring the health of patients typically in cardiovascular diseases, cancer detection, glucose level monitoring, and asthma and organ monitoring. Compared with the existing technologies such as WLAN, WBAN enables the communication around the human body by using wireless computing devices [4].

The communication in WBAN is classified into two subtypes including intrabody communication and extrabody communication. The multitier architecture of the wireless body area network has been designed for health care systems are mentioned as follows in Figure 1. The four-tier architecture consists of an intrabody sensor network communication module referred as Tier-1. Tier-1 consists of sensor nodes deployed on the human body. The sensors deployed on the human body are ECG sensors, ear sensors, blood pressure sensors, ECG sensors, EMG sensors, and body motion sensors. Tier-2 consists of the interbody sensor network communication module referred to as the access point. This module is responsible to receive the health status information from Tier-1 and routes this information to Tier-3. Tier-3 consists of the beyond body network communication-based infrastructure. This module is responsible for transferring data from Tier-2 (access point) to Tier-3. Tier-3 is also responsible for providing wireless health care services by using the Internet [2]. Tier-3 also consists of the data management unit for analysis and intelligent decision-making by doctors and emergency rescue staff at hospital located within Tier-4 [5].

2. Related Work

The goal of this section is to provide the literature review which is based on the description of the existing routing schemes related to WBAN. In this chapter, routing schemes related to WBAN are discussed which are based on WSN. The efficiency and reliability of WBAN depends on the system response, to send and receive the information between the sensor nodes, which eventually depends on the selected routing scheme or protocol to be used. Although many routing schemes had been designed for WSNs but neither any energy-efficient scheme/protocol had been designed for WBAN. For the WBAN framework, the major focus is on minimal routing overhead, minimum energy consumption, and maximum throughput. WSNs are typically designed for homogenous networks, and WBANs are designed for heterogeneous networks. The classification of routing protocols for WBAN is based on multiple schemes. The routing protocols in WBAN are classified into further subtype-based routing topologies. The classification includes QoS aware routing protocols, temperature aware routing protocols, cluster-based routing protocols, postural movement based routing protocols (cost-effective routing), and cross-layered routing protocol [4]. The lifetime of biomedical sensor nodes contributes towards an important role in healthcare applications [1]. The small thermal and battery-powered sensor nodes, working in ad hoc infrastructure, provides the maximum benefit when they communicate with each other for the maximum amount of time [6]. The larger area of the network provides an optimal interface for sensor nodes to communicate with each other and monitors the maximum amount of events in ad hoc wireless infrastructure [7, 8], where the routing technique plays an important part in the energy efficiency of wireless sensor nodes [9]. In WBAN, the shortest path selection within multiple clusters is the optimal routing strategy used within ad hoc wireless infrastructure. The routing protocol and clustering technique should be flexible enough that if we could add additional sensor nodes in the network field, it should be capable of routing the data efficiently from one node to another within each cluster [10, 11]. Typically, wireless sensor nodes avoid direct communication with the head node or sink node due to the high-energy consumption factor [12]. It is feasible that sensor nodes communicate with other sensor nodes to communicate with a head node within each cluster [13]. In many WBAN-based applications as the energy of sensor nodes is depleted, the performance of the network becomes degraded. The reason is the power dissipation over the head of sensor nodes. Latest WBAN protocols can cater to this communication overhead [14, 15]. The core objective of the data aggregation technique in WBAN is to gather the data by the sink node in an energy-efficient manner so that the network lifetime is enhanced [16].

3. Classification of Routing Protocols in WBAN

The classification of routing protocols will be categorized in different categories which are based on research challenges related to WBAN. Figure 2 describes about the existing routing schemes, which are mainly categorized as cluster-based routing, postural movement based routing, cross-layered routing, quality of service (QoS) aware routing, and temperature-aware routing schemes [19].

4. Comparison and Evaluation Criteria for Energy-Efficient Routing Protocols

Section 4 describes in deep detail about the comparison and evaluation framework. The evaluation framework in this research study is based on the parameters as described in Table 1. The framework parameters to be considered includes energy efficiency, routing, clustering, communication and network infrastructure, delay and packet loss ratio, security, and types of the wireless sensor network used. Each evaluation framework parameter is further subclassified into subparameters based on its functionality. This section describes the detailed information about the analysis and discussion based on the literature review. The evaluation framework parameters are based on energy efficiency techniques in wireless body area networks. The evaluation framework parameters are energy efficiency, routing, clustering, communication and network Infrastructure, delay packet loss ratio, security, and wireless sensor network type used. The evaluation framework parameters are allocated score based on their core functionality and deployment in health care applications. The evaluation framework parameters are also subcategorized into subparameters along with the score allocated for each subdivision parameter.

Table 2 describes about the grading and classification of existing routing protocols in WBAN.

The energy efficiency classification is based on the further subdivision parameters including single-/multihop communication, quality of service, real time delay, and radio optimization technique used. Ahmed et al. [14] had achieved the highest score in the energy efficiency framework table based on subdivision parameter classification. Ahmad et al. [9] had also achieved the second highest score in the energy efficiency framework table but neglecting an important subdivision parameter named as quality of service in energy-efficient wireless body area networks. Table 2 describes about the routing information subparameter classification table. The routing table is based on further subdivision parameters including location-based routing, multipath-based routing, and quality of service-based routing. Ahmad et al. [14], Haseeb et al. [15], and Chen [24] had achieved the highest score and focused their research on using energy-efficient routing schemes in wireless body area sensor networks. The clustering table is based on further subdivision parameters including topology for single-hop/multihop communications and cluster head selection. Ahmad et al. [9] had achieved the highest score in the clustering table and contributes its important role in energy-efficient routing and clustering techniques in wireless body area sensor networks. Table 2 describes about the communication and network infrastructure subparameter classification table. The communication and network infrastructure is based on further subdivision parameters which includes the wireless sensor network coverage area [39]. The coverage area may be triangular, square, and hexagonal for sensor network deployment. The second subdivision parameter is the energy consumption factor in case of the wireless body area sensor network during the communication purpose for a designated coverage area. The last subdivision parameter is the medical wireless sensor network deployment scheme used during the health care sensor network communications. Khan et al. [6], Sahndhu et al. [7], Elias [13], Sabel et al. [20, 40], and Kim and Lee [31] had critically analyzed and deployed the medical sensors within the designated coverage area using an energy-efficient wireless sensor network scheme [41]. The delay packet loss ratio can also be further categorized into subdivision parameters including RSSI (received signal strength intensity), hop count, and per hop round trip time. Ling et al. [8], Javid et al. [10], Bradi et al. [12], Elias [13], Haseeb et al. [15], Zeng and Dong [25], and Javed et al. [29, 30] had achieved the highest score in the delay packet loss ratio related to wireless body area sensor networks in the health care domain [42, 43]. Security issues can further be subcategorized into subdivision parameters including confidentiality, integrity, authentication, and access control/nonrepudiation [44, 45]. Raja and Kiruthika [23] had achieved the highest score in security issues using encryption and decryption schemes for health care using wireless sensor networks. WSN for health care systems can further be categorized into subdivision parameters including homogenous wireless sensor networks and heterogeneous wireless sensor networks. Ahmad et al. [9], Javaid et al. [10], and Chen [24] had achieved the maximum score in wireless sensor network types and its deployment scheme in health care networks by using na energy-efficient framework [46, 47]. Figure 3 describes the graphical representation of evaluation framework parameters’ total score versus reference based on the research work.

5. Conceptual Model for Energy-Efficient Framework for Wireless Body Area Sensor Networks (WBAN)

The conceptual model for the energy-efficient framework for wireless body area sensor networks is designed by using a five-tier framework architecture as mentioned in Figure 4 below.

6. Simulation Results and Experimentation

This section provides a comparative analysis of the proposed protocol (M-DSDV-RMCP) with existing routing protocols DSDV and RMCP. The simulation results had been obtained in MATLAB version 12.0. The simulation results obtained are based on the number of packets sucessfully transmitted versus 200 numbers of iterations as shown in Figure 5.

From the simulation results, it has been observed that the performance of the M-DSDV-RMCP protocol is better than the DSDV and RMCP routing protocols due to the maximum no. of packets transmitted from the source node to the sink node.

7. Conclusions and Future Work

The conclusions of the research work is based on the development of the RMCP protocol, which is capable to successfully route the data from the access point to the base station in layer 3. These results in the successful packet delivery ratio from layer 3—which is communication infrastructure towards layer 4—which is the health care information system for strong analysis and decision-making by doctors and health care institutions at layer 5. The new protocol is assumed to be named as the modified version of the DSDV protocol based on the RMCP protocol. The M-DSDV-RMCP-based routing protocol supports a successful packet delivery ratio between layer 3 and layer 4. The future work relies on the integration of IOMT (Internet of Medical Things).

Conflicts of Interest

The authors declare that they have no conflicts of interest.