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M-ATTEMPT: A new energy-efficient routing protocol for wireless body area sensor networks

Authors:

Abstract

In this paper, we propose a new routing protocol for heterogeneous Wireless Body Area Sensor Networks (WBASNs); Mobility-supporting Adaptive Threshold-based Thermal-aware Energy-efficient Multi-hop ProTocol (M-ATTEMPT). A prototype is defined for employing heterogeneous sensors on human body. Direct communication is used for real-time traffic (critical data) or on-demand data while Multi-hop communication is used for normal data delivery. One of the prime challenges in WBASNs is sensing of the heat generated by the implanted sensor nodes. The proposed routing algorithm is thermal-aware which senses the link Hot-spot and routes the data away from these links. Continuous mobility of human body causes disconnection between previous established links. So, mobility support and energy-management is introduced to overcome the problem. Linear Programming (LP) model for maximum information extraction and minimum energy consumption is presented in this study. MATLAB simulations of proposed routing algorithm are performed for lifetime and successful packet delivery in comparison with Multi-hop communication. The results show that the proposed routing algorithm has less energy consumption and more reliable as compared to Multi-hop communication.
Procedia Computer Science 19 ( 2013 ) 224 231
1877-0509 © 2013 The Authors. Published by Elsevier B.V.
Selection and peer-review under responsibility of Elhadi M. Shakshuki
doi: 10.1016/j.procs.2013.06.033
The 4th International Conference on Ambient Systems, Networks and Technologies
(ANT 2013)
M-ATTEMPT: A New Energy-Ecient Routing
Protocol for Wireless Body Area Sensor Networks
N. Javaid1,, Z. Abbas1, M. S. Fareed1,Z.A.Khan
2, N. Alrajeh3
1COMSATS Institute of Information Technology, Islamabad, Pakistan.
2Faculty of Engineering, Dalhousie University, Halifax, Canada.
3B.M.T., C.A.M.S, King Saud University, Riyadh, Saudi Arabia.
Abstract
In this paper, we propose a new routing protocol for heterogeneous Wireless Body Area Sensor Networks (WBASNs);
Mobility-supporting Adaptive Threshold-based Thermal-aware Energy-ecient Multi-hop ProTocol (M-ATTEMPT). A
prototype is defined for employing heterogeneous sensors on human body. Direct communication is used for real-time
trac (critical data) or on-demand data while Multi-hop communication is used for normal data delivery. One of the
prime challenges in WBASNs is sensing of the heat generated by the implanted sensor nodes. The proposed routing al-
gorithm is thermal-aware which senses the link Hot-spot and routes the data away from these links. Continuous mobility
of human body causes disconnection between previous established links. So, mobility support and energy-management
is introduced to overcome the problem. Linear Programming (LP) model for maximum information extraction and
minimum energy consumption is presented in this study. MATLAB simulations of proposed routing algorithm are per-
formed for lifetime and successful packet delivery in comparison with Multi-hop communication. The results show that
the proposed routing algorithm has less energy consumption and more reliable as compared to Multi-hop communica-
tion.
c
2011 Published by Elsevier Ltd.
Keywords: Wireless Body Area Sensor Networks, Threshold-based, Thermal-aware, Multi-hop, Single-hop
1. Introduction
Patient monitoring is emerging as an important application of embedded sensors network. Many wireless
sensors are implanted in/on the patient body. These tiny wireless sensors make Wireless Body Area Sensor
Networks (WBASNs). A WBASNs can observe physiological conditions of patient under supervision, and
can provide us real-time feedback. Through WBASN a patient is constantly monitored, and in case of some
critical situation an immediate action should be required. These sensors can collect the physiological data
and then send to physician in a hospital through Metropolitan Area Network (MAN) or Local Area Network
Email address: nadeemjavaid@comsats.edu.pk, nadeemjavaid@yahoo.com (N. Javaid)
URL: http://www.njavaid.com (N. Javaid)
Available online at www.sciencedirect.com
© 2013 The Authors. Published by Elsevier B.V.
Selection and peer-review under responsibility of Elhadi M. Shakshuki
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N. Javaid et al. / Procedia Computer Science 19 ( 2013 ) 224 – 231
(LAN). Where, diagnosis from received information is performed and on that base decisions are taken.
WBASNs are used for medical and non medical applications. The wireless sensor nodes used in WBASNs
are tiny, light-weight and of limited power. These sensor nodes have dierent energy levels and generate
dierent size of data while the Wireless Sensor Networks (WSNs) nodes almost have same level of energy
and data rate. Thus, employing routing algorithm of WSN can not support WBASNs sensor nodes. The
selection of WBASNs routing algorithms should support the heterogeneous sensors network.
In [1], Single-hop communication is used between sensor nodes and sink node. To overcome the problem
of topological partitioning due to constant human body movement and ultra short Radio Frequency (RF)
transmission range. Sue et al. [2] used Multi-hop communication for communication between sink and
root nods. However, In direct communication increase in temperature of sensor nodes may aect human
body tissues. He also discussed that storage delay (due to topological disconnections) and congestion delay
increase overall delay in Multi-hop communication that can not be helpful for emergency services and makes
Multi-hop communication not a best choice.
In this paper, a prototype for placing heterogenous sensor nodes on human body is presented. High data
rate nodes are placed on less mobile places on human body. Mobility of human body cause disconnection
between previous established links. It takes time to establish new connection to forward data and causes
delay. Delay is not supportive in real-time applications. To beat delay and overcome problem of disconnec-
tion. We used energy management in our proposed routing protocol. By using energy management sensor
nodes increase their transmission range and directly communicate with sink node for critical data delivery.
For normal data delivery Multi-hop communication is used.
2. Background and Motivation
The rising temperature of implanted sensor nodes due to communication radiations and circuitry power
consumption can aect the human body. In [3], authors use thermal-aware routing to minimize the eect
of rising temperature of implanted sensor nodes. Quwaider et al. [4] used Single-hop communication and
increased transmission range of sensors to overcome problem of partitioning.
Environment Adaptive Routing (EAR) algorithm [5] defines dierent communication cost for heteroge-
neous WBASNs devices. However, the Single-hop communication and proactive routing are not suitable
choices for WBASNs. Multi-hop communication is suitable for normal packet delivery and Single-hop is
only used for emergency services due to high transmission cost. However, here use of Hello messages after
a regular interval results in high energy consumption.
In [6], Wireless Autonomous Spanning Tree Protocol (WASP) is defined to achieve low delay and in-
creased network reliability for WBASNs. In WASP-scheme a message is disseminated to update parent
nodes with information of its child nodes. However, power balancing issue is not discussed. Annur et al.
[7] applied tree algorithm with prioritization for WBASNs. Where, a channel is dedicated for emergency
data delivery and normal data transmission is lagged until the successful delivery of critical data. However,
the dedicated channel results in loss of available resources.
In this study, we present a routing protocolwhich works better in heterogeneous as well as homogeneous
network. The nodes are placed around the sink in descending order of their data rate. A priority mechanism
is used where low data rate sensors can not forward their data until all emergency data is transferred. To
overcome delay, critical data is sent directly to the sink node and normal data is sent through Multi-hop
communication. Our proposed model is discussed in next section.
3. System Model
In our proposed model, sink is placed at center of the human body. Since Wireless Body Area Sensor
Networks (WBASNs) are heterogeneous networks, then placement of nodes on human body is an issue.
This issue is resolved by placing nodes in descending order of their data rate with respect to sink. Thus,
the nodes with high data rate send data directly to the sink node, and can easily forward the received data
from low data rate sensors. Problems analyzed in previous work are set in following manner: (1) Single-hop
226 N. Javaid et al. / Procedia Computer Science 19 ( 2013 ) 224 – 231
communication is used for emergency services and on-demand data, (2) for normal data delivery Multi-hop
communication is used, (3) path with less hop count is selected for network life time extension in Multi-hop
communication. Fig. 1 depicts the phases of proposed routing protocol with above mentioned features.
Complete description of the proposed routing protocol is provided in next section.
3.1. Initialization Phase
In initialization phase, all nodes broadcast Hello messages. This Hello message contains neighbors
information and distance of sink nodes in form of hop-counts. In this way, all nodes are updated with their
neighbors, sink position and available routes to the sink node. Route computation for data delivery to sink
node of the proposed routing algorithm is discussed in next subsection.
   
       
Fig. 1. Sequence of Phases in Each Round
3.2. Routing Phase
In this phase, routes with fewer hops to sink are selected from available routes. We suppose nodes have
information of all nodes and sink’s position. So, selected routes are steadfast and consume less energy.
Emergency services are also defined in proposed routing protocol. In critical scenarios, all processes are
lagged until critical data is successful received by sink node. In case of emergency, all the implanted nodes
on the body can communicate directly with the base station. Moreover, all sensor nodes can communicate
directly with the sink node when demand is arrived from sink. In direct communication, delay is much lower
as compared to Multi-hop communication, because in Multi-hop communication, each intermediate node
receives, processes and then sends data to next node. The reception, processing and transmission of received
data on each intermediate node takes time which causes delay. Sometime, this delay is also increased due
to congestion and becomes unacceptable in some critical scenarios. So, single-hop communication is used
to minimize this delay. We calculate energy consumed in Single-hop communication as:
ESHOP =Etransmit (1)
where, the transmission energy is calculated as:
Etransmit =Eelec +Eamp (2)
where, Eelec is the energy consumed for processing data and Eam p is energy consumed by transmit
amplifier. We suppose a linear network in which all nodes are implanted at equal distance from each other.
To transmit bbits up to nhops the transmission energy is given as:
where d2is the energy loss due to the transmission.
Etransmit =n×b(Eelec +Eamp )×d2(3)
In Single-hop/Multi-hop trac control algorithm 1, if a node senses emergency or on-demand data, node
uses Single-hop communication. In Single-hop communication, the sensor node uses full power of battery
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N. Javaid et al. / Procedia Computer Science 19 ( 2013 ) 224 – 231
Fig. 2. Link Hot-spot Detection
to send its data. If normal data is received, the Multi-hop communication is used to send data to sink node,
which results in less energy consumption. More energy is required to send data at greater distances. Thus,
in Multi-hop communication, energy consumption is very less.
Energy preservation is a prime consideration in WBASNs, as the deployed sensor nodes have limited en-
ergy sources. So, deployed nodes need reasonable use of battery for extended network life time. To calculate
the energy consumption during a Multi-hop communication we assume a linear network in which all nodes
are deployed at equal distance from each other. The energy consumption during Multi-hop communication
can be computed using the following equations:
EMHOP =Etransmit +Ereceived (4)
where, Ereceived is the energy consumed for receiving data. If we are transmitting b-bits to a distance of
n-hops the transmission energy will be n×b×Etransmit and receiving energy will be (n1)b×Ereceived.Since
the first node transmits only and intermediate nodes receive n-bits and then transmit these received bits. So,
the energy consumed for Multi-hop is:
EMHOP =n×b×Etransmit +(n1)b×Ereceived (5)
From (2) and (6), taking Ereceived =Eelec since the receiving energy is equal to energy consumed to
process received data we obtain
EMHOP =n×b×(Eelec +Eamp ×d2)+(n1)b×Eelec (6)
EMHOP =n×b×Eelec +n×b×Eamp ×d2+nb ×Eelec b×Eelec (7)
EMHOP =[2 ×n×b×Eelec +nb ×Eamp ×d2b×Eelec](8)
When we are dealing with wireless communication around the human body, eects of these sensors on
human body can also be taken into consideration. The most important considered factor for this purpose is
Specific Absorption Rate (SAR) and heating eects of the implanted sensor nodes on human body. Taking
SAR and heating eects of sensors on human body in mind, we considered and implemented link hot-spot
228 N. Javaid et al. / Procedia Computer Science 19 ( 2013 ) 224 – 231
detection method. Here, nodes implanted closer to sink node are forwarding data of their follower nodes.
Whenever, a temperature threshold is reached, a node breaks its link with its neighbor for few rounds. As
temperature returns to normal, it re-establishes the original route. However, if a sensor node receives a data
packet and reaches its temperature threshold it returns packet to previous node. And previous node mark
this link as Hot-spot as shown in Fig. 2.
Algorithm 1 : ATTEMPT Algorithm
1: Routing Phase
2: if ( route 1<route 2)then
3: route 1=selected route
4: else
5: route 2=selected route
6: if ( route 2 <route 1)then
7: route 2=selected route
8: else
9: route 1=selected route
10: if ( route 1=route 2)then
11: Ehopcount Energy consumption for a route
12: if (Ehopcount 1<Eho pcount 2)then
13: route 1=selected route
14: else
15: route 2=selected route
16: end if
17: end if
18: end if
19: end if
ATTEMPT routing is discussed in Algorithm 2. If two routes are available then route with less hop-
counts is selected. If two routes have same hop-count, then route with less energy consumption to the sink
is selected. Single-hop and Multi-hop communication of root node with sink is shown in Fig. 3.











 



Fig. 3. Energy Management for Single-hop and Multi-hop Communication
3.3. Scheduling Phase
After route selection the sink node creates Time Division Multiple Access (TDMA) schedule for commu-
nication between sink node and root nodes. Sink node allocate time-slots to nodes. Nodes can communicate
to sink node in assigned time slot for normal data delivery.
3.4. Data Transmission Phase
Once the time slots are allocated to root nodes, root nodes send their data to sink node in assigned time
slot. After that sink node will receive data, and will take some time to aggregate the received data.
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N. Javaid et al. / Procedia Computer Science 19 ( 2013 ) 224 – 231
4. Mobility Support in ATTEMPT
To introduce mobility support in ATTEMPT, we defined a prototype for placing nodes on human body
for Mobile-ATTEMPT (M-ATTEMPT). Nodes with high data rates are placed at less mobile places on
human body. These high data rate nodes are parent nodes and are directly connected to sink. Parent nodes
have 10Jenergy and generate 10 Kbytes of data. The nodes directly connected to parent nodes are first
level child-nodes with 5Jenergy and generate 1 Kbyte of data. The nodes connected to first level nodes are
second level child-nodes with 1Jenergy and generate 50 bytes of data. Parent nodes, first level child-nodes
and second level child nodes placed on human body and their respective topology is shown in Fig. 3.

   
    
 


 


 

 



   
    
 


  


 






   
    
 


 



 





   
Fig. 4. Link Establishment and Link Breakage Due to Mobility of Human Body
4.1. Invitation Phase
In this phase, we will discuss how our proposed routing protocol support mobility. if a node changes
its position during a round, nodes have to pay lot of energy to maintain this established link. Consider an
example where, first level child node C4 is disconnected from its parent node P2 and entered in communi-
cation range of parent node P1. Now C4 will send joint-request to parent node P1. Parent node will check
its parent child list if number of child nodes are less than 3. Then, parent node P1 will accept joint-request
and register C4 as a child node as depicted in Fig. 4.
5. Simulation Results
We performed series of simulations to compare performance of our proposed routing protocol with
Multi-hop. We used MATLAB as a simulator to analyze the performance of proposed routing protocol. We
took network size of 5m×5min which 10 nodes are randomly distributed and sink node is placed in the
center of the network. 5000 number of rounds taken and nodes with initial energy of nodes 0.5Jand radio
range of 10m
The time in which all nodes in network are alive is called the stability period of network. M-ATTEMPT
in sense of network life time performs best as long as compared to Multi-hop communication and has
almost greater lifetime as compared to ATTEMPT. Number of dead nodes are presented as function of
rounds. Round is time required to establish a network, here probability for network establishment is kept to
be 10%. Where after this value node can be selected as CH. So, taking this parameter first node dies out at
2700 round for M-ATTEMPT as compared to others. M-ATTEMPT has better stability period as compared
to Multi-hop routing or ATTEMPT as depicted in Fig. 5.
A Multi-hop routing is the best choice for WBASNs. Here, in our proposed routing protocol single-
hop and multi-hop both concepts are being used. So, Throughput of both techniques implemented with
230 N. Javaid et al. / Procedia Computer Science 19 ( 2013 ) 224 – 231
0500 1000 1500 2000 2500 3000 3500 4000 4500 5000
0
2
4
6
8
10
Number of Rounds
Number of Dead Nodes
Multihop
ATTEMPT
M−ATTEMPT
Fig. 5. Number of Dead Nodes Over Time
0500 1000 1500 2000 2500 3000 3500 4000 4500 5000
0
500
1000
1500
2000
2500
3000
3500
Number of Rounds
Packets Sent to BS
Multihop
ATTEMPT
M−ATTEMPT
Fig. 6. Throughput
mobility support is experimentally investigated, by measuring the successful packets delivery at BS. Fig.
6 depicts that throughput of M-ATTEMPT is almost better in stable and unstable region than ATTEMPT
and Multi-hop communication. ATTEMPT sends threshold data and periodic data, so its throughput is
estimated from this data. In multi hop communication only periodic data is received at sink node. While,
M-ATTEMPT which uses Single-hop and Multi-hop communication with mobility management performs
better as compared to Multi-hop and ATTEMPT. In case, if link is broken because of mobility, M-ATTEMPT
establishes link with another node by checking hop counts or on minimum energy usage basis. So, no loss
of packets occur in case of link breakage.
0500 1000 1500 2000 2500 3000 3500 4000 4500 5000
0
2
4
6
8
10
12
Number of Rounds
Number of CH per Round
Multihop
ATTEMPT
M−ATTEMPT
Fig. 7. Number of Cluster Heads Per Round
Fig. 7 shows number of selected CH in each round for all three protocols. Here, M-ATTEMPT shows
maximum CH selection in some rounds, as in some rounds there are still chances for CH selection for other
nodes. Total energy consumption of M-ATTEMPT, ATTEMPT and multi hop communication is depicted
in Fig. 8. M-ATTEMPT utilizes maximum energy as nodes start dying after reaching maximum rounds as
compared to ATTEMPT and Multi-hop communication.
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0500 1000 1500 2000 2500 3000 3500 4000 4500 5000
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Number of Rounds
Total Energy of Network (J)
Multihop
ATTEMPT
M−ATTEMPT
Fig. 8. Total Energy of Network over Varying Rounds
Finally, a comparison in terms of percentage between all protocols is discussed. Results of all three tech-
niques clarifies that our proposed protocol’s stability period is 20% greater as compared to Multi-hop and
11% greater in comparison with ATTEMPT over changing rounds. This is because that our proposed proto-
col uses Single-hop and Multi-hop with mobility management technique. When comparison between num-
ber of successfully received packets at sink is performed between all three techniques, then M-ATTEMPT
shows a 29% better results as compared to Multi-hop and 12.5% with ATTEMPT. M-ATTEMPT as com-
pared to others has 29.5% better network life time over varying number of rounds.
6. Conclusion
In this work, we presented an energy ecient routing algorithm for heterogeneous WBASNs. For real-
time and on-demand data trac root node directly communicates with sink node and for normal data de-
livery Multi-hop communication is used. Our proposed routing protocol supports mobility of human body
with energy management. The proposed routing algorithm is thermal-aware which senses the link Hot-spot
and routes the data away from these links. After selection of routes sink node creates TDMA schedule for
communication between sink node and root nodes for normal data delivery using multihop communication.
MATLAB simulations of proposed routing algorithm are performed for lifetime and packet delivery ratio in
comparison with Multi-hop communication. Topology and placement of nodes is described with Single-hop
and Multi-hop communication scenarios. The results show that proposed routing algorithm has less energy
consumption and more reliable in sense of packet delivery as compared to Multi-hop communication.
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... But when there are too many hot-spot regions, the routing protocol only considers a few nodes to establish the routing path, which may lead to hypo-optimum path and increase of energy consumption. Other temperaturebased routing protocols include Mobility-supporting Adaptive Threshold-based Thermal-aware Energyefficient Multi-hop Protocol (M-ATTEMPT) [20] and TTRP [5]. These protocols all consider temperature as the basic weight to achieve the balance of communication between nodes, but their shortcomings are the lack of comprehensive consideration of reliability and energy efficiency. ...
... When the data rate is 5 packet/ s, compared with OCER and SHT, EERR-RLFL delays the death time of the first node by 12% and 23% respectively. For the case of data rate = (10,15,20,25,30) packet/s, EERR-RLFL yields 16%, 3%, 10%, 5% and 5% longer lifetime over OCER, and 19%, 6%,17%,10% and 7% longer lifetime over SHT. It can be concluded that if the network lifetime is defined by the death time of the first node in the network, EERR-RLFL can extend the network lifetime no matter what the data rate is. ...
... In addition, Fig. 20 shows a comparison of network lifetime defined in terms of the time when 50% of the nodes in the network die. When data rate = (5,10,15,20,25,30) packet/s, EERR-RLFL extends the network lifetime by 5%, 4%, 5%, 2%, 2% and 3% over OCER, and by 6%, 5%, 11%, 4%, 3% and 6% over SHT. After that, we also captured the time when all nodes in the three protocols died under different data rates, as shown in Fig. 21. ...
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In Wireless Body Area Networks (WBANs), on the one hand, the energy of nodes is limited. On the other hand, the network topology often changes due to human movement or posture changes. Unstable network topology is easy to cause packet loss, and packet loss will cause inaccurate data collection. Therefore, how to effectively use energy to transmit data reliably becomes a key issue. For this problem, we propose an optimized routing protocol namely Energy Efficient and Reliable Routing based on Reinforcement Learning and Fuzzy Logic (EERR-RLFL). In EERR-RLFL, considering the heterogeneity of nodes in WBANs, we first establish a node rank division mechanism, by which sensor nodes are divided into different ranks from three aspects. Each rank is considered to be one of the factors that affect the link quality. Then, we propose the Fuzzy-Logic-based Link Quality Evaluation (FLLQE) algorithm. It makes use of the fuzzy evaluation method of fuzzy logic and considers the comprehensive influence of multiple factors to evaluate the link quality between two nodes, which will provide reference for routing path selection. In the process of data transmission, based on the FLLQE algorithm, we use a hybrid data transmission mode, in which the time when a forwarding node is needed is first determined, and then the Reinforcement Learning algorithm is used to select the global optimized routing path. Simulation results show that EERR-RLFL outperforms Single Hop Transmission and Optimized Cost Effective and Energy Efficient Routing in terms of network lifetime, packet loss ratio and energy efficiency.
... Various researchers have attempted to overcome the challenges in various ways. For example, authors [26][27][28] employed line-of-sight (LoS) and no-line-of-sight (NLoS) communications, single-hop routing schemes, and multi-hop routing schemes to solve this problem, whereas authors [29,30] used storage and forwarding routing. As a result, the proposed routing protocols must be able to accommodate various topological changes. ...
... The protocol in [27] is both temperature-aware and energyefficient, and supports mobility and energy management using An example of least total-route temperature (LTRT) [54] the linear programming (LP) method for the greatest information extraction while consuming the least amount of energy. Here, network lifetime has been increased compared to the case in multi-hop. ...
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The growth of the world's population, especially that of the elderly, along with the outbreak of infectious diseases such as COVID‐19 have caused hospitals and healthcare centres to become full, and even economical treatments cost a lot. On that account, the conjunction of wireless body area networks (WBAN) and Internet of Things (IoT) for healthcare and medical diagnosis has become really important, and is accordingly one of the most popular and attractive areas of the Internet of Things (IoT). In such an IoT, a wireless body area network (WBAN) consists of a miniature sample of the Internet of Medical Things (IoMT) that can be either implanted in the human body or wearable. Nowadays, IoT has made healthcare evaluation possible. Instead of the patient being constantly hospitalized for treatment, the condition of the person is sent to the health centre by the IoMT over the Internet. IoT enables wireless communication between smart devices on one side and almost anything on the other. Since this network deals with medical and critical conditions, data must be sent to a physician or practitioner in the prescribed period; this indicates that routing is one of the most critical issues. Thus, routing is considered a very important challenge in WBANs. The present study describes thermal (temperature)‐aware routing protocols in WBANs. Routing protocols in WBANs are divided into thermal (temperature)‐aware, QoS‐aware, security‐aware, cluster‐based, cross‐layered, postured‐based, cost‐effect, link‐aware, and opportunistic ones. In a WBAN, temperature rise in implant nodes can damage body tissues, which is dangerous for the patient. Accordingly, here, those algorithms were considered which are presented in thermal (temperature)‐aware protocols. This paper first introduces IoT‐based WBANs, their routing mechanism and challenges, after which it provides a detailed description of thermal (temperature)‐aware algorithms. Finally, the advantages and disadvantages of these algorithms are presented.
... As a result, possible link or packet recovery is a fundamental responsibility of a protocol to achieve two-way successful cooperation between nodes. The complete scenario is computed in (20). ...
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Implanted biological sensors are a special class of wireless sensor networks that are used in-vivo for various medical applications. One of the major challenges of continuous in-vivo sensing is the heat generated by the implanted sensors due to communication radiation and circuitry power consumption. This paper addresses the issues of rout- ing in implanted sensor networks. We propose a thermal-aware routing protocol that routes the data away from high temperature areas (hot spots). With this protocol each node estimates temperature change of its neighbors and routes packets around the hot spot area by a withdraw strategy. The proposed protocol can achieve a better balance of temper- ature rise and only experience a modest increased delay compared with shortest hop, but thermal-awareness also indicates the capability of load balance, which leads to less packet loss in high load situations.
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This paper presents a location based store-and-forward packet routing algorithm for wireless body area networks (WBAN) with frequent postural partitioning. A prototype WBAN has been constructed for experimentally characterizing on-body topology disconnections in the presence of ultra short range radio links, unpredictable RF attenuation, and human postural mobility. A location based packet routing protocol is then developed. The performance of the proposed protocol is evaluated experimentally, and is compared with a generic probabilistic routing protocol and a specialized on-body packet flooding mechanism that provides the routing delay lower-bounds. It is shown that via successfully leveraging the node location information, the proposed algorithm can provide better routing delay performance compared to existing probabilistic routing protocols in the literature.
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On-body packet routing algorithms for body sensor networks, in: Networks and Communications doi:10.1109/NetCoM
  • M Quwaider
  • S Biswas
  • M Quwaider
  • S Biswas
An energy-efficient configuration management for multihop wireless body area networks
  • S.-H Seo
  • S Gopalan
  • S.-M Chun
  • K.-J Seok
  • J.-W Nah
  • J.-T Park
S.-H. Seo, S. Gopalan, S.-M. Chun, K.-J. Seok, J.-W. Nah, J.-T. Park, An energy-efficient configuration management for multihop wireless body area networks, in: Broadband Network and Multimedia Technology (IC-BNMT), 2010 3rd IEEE International Conference on, 2010, pp. 1235 1239. doi:10.1109/ICBNMT.2010.5705287.