A survey of real-time routing protocols For wireless sensor networks

International Journal of Computer Science & Engineering Survey (IJCSES) Vol.4, No.3, June 2013
DOI : 10.5121/ijcses.2013.4303 35
A SURVEY OF REAL-TIME ROUTING PROTOCOLS
FOR WIRELESS SENSOR NETWORKS
Sandhya Rachamalla1
Dr. Anitha Sheela Kancharla2
1
Department of Electronics and Communications Engineering, Sreenidhi Institute of
Science and Technology, Hyderabad, Andhra Pradesh, India
2
Department of Electronics and Communications Engineering, JNTUH, Hyderabad,
Andhra Pradesh, India
reddysandhya28@gmail.com
ABSTRACT
Sensor networks is an interdisciplinary research area that draws on contributions from signal processing,
wireless networking and associated routing protocols, database management and information systems,
distributed algorithms and MEMS technology. Recent developments in Wireless Sensor Networks have
resulted in wide variety of real- time applications. Many real-time routing protocols are designed to meet
the requirements of these applications where timely delivery of the sensed information is given the top
priority. This paper presents the comparative analysis of various existing real-time routing protocols for
wireless sensor networks, which emphasizes on various factors like end-to-end delay, energy, mobility,
scalability and highlighted various challenges for future research.
KEYWORDS
Wireless Sensor Networks (WSNs), Micro-Electro Mechanical Systems (MEMS), Real-time routing (RT),
Routing protocols (RPs), QoS, Dead line miss ratio (DMR), Energy consumption, Void avoidance, end-to-
end delay
1. INTRODUCTION
Advances in wireless networking and MEMS technology have enabled a new generation of
massive-scale sensor networks suitable for wide range of applications. Unlike a centralised
system, a sensor network is subject to a unique set of resource constraints such as battery power,
limited network bandwidth and a small amount of memory for signal processing and task
scheduling. Applications of sensor networks are wide range and can vary significantly in
application requirements, sensing modality and node deployment. Some of the applications are
environmental data collection, habitat exploration of animals, Security monitoring, guiding
systems of missiles, detection of hidden weapons, patient diagnosis, flood detection,
infrastructure protection, battle field awareness, home automation, context aware computing.
Examples of real time sensor applications can be found in many commercial systems, military,
surveillance systems and safety critical systems [1]. In target tracking applications of Wireless
Sensor Networks the collected data must reach the base station or control unit in predefined time
to ensure an effective real time tracking of the required sensed region [2].In medical applications,
sensed data can be sent regularly over the network to the automated monitoring systems which
are designed to alert the concerned doctor [3]. In these applications, timely and reliable data
delivery is very important for positive results. Designing of the real-time routing protocol for

36
WSN is a challenging task as WSN is energy constrained due to the tiny battery power while RTs
demand more power. Both of these constraints, energy and time, are inversely proportional to
each other. On-time delivery of sensed information requires maximum transmission power.
The MAC layer mechanisms deliver the information by considering real time needs, but effect
remains locally. Therefore the real-time routing protocol has to guarantee on-time delivery
globally. Hence, the designing of a real-time routing protocol for WSNs with optimum energy
consumption is a challenging task. In paper [4], authors stated various design issues like data
delivery model, node deployment, energy consumption, fault tolerant, scalability and other QoS
to be considered while designing the real time routing protocol.
2. REAL- TIME ROUTING PROTOCOLS
Many researchers have provided solutions for real-time routing in WSNs. This section provides
the comparative analysis of the various existing real time routing protocols for WSNs
emphasizing their strengths and weaknesses and various other challenges. Real time routing is
discovering an optimum route from source to destination which meets the real time constraints.
Timely and reliable data delivery is very important for positive results as out-dated data may lead
to disaster effects.
2.1. Ad hoc On-Demand Distance-Vector (AODV) Routing algorithm
AODV [5] is an on-demand routing protocol which builds route between the nodes only when the
source node demands for routing the sensed data. And as long as required by the source node the
routes are maintained. This routing algorithm provides the tree formation connecting the multicast
members. It uses the sequence numbers to ensure the freshness of the routes resulting in loop-free
routing.
In this protocol, as shown in Figure 1 (a), RouteRequest packets are broadcasted by the source
node when the route is not available from source to the destination. From this it may obtain
multiple routes to the destination for a single RouteRequest. A sequence number called
destination sequence number (DestSeqNum) is used in RouteRequest packets to determine the
latest path to the destination. After receiving RouteRequest packet with DestSeqNum, an
intermediate node verifies it and updates only if received sequence number is greater than the last
stored one. And an intermediate node upon receiving a RouteRequest, it either forwards it or
prepares a RouteReply, as shown in Figure 1 (b), if it already has a valid route to the destination.
The validity of a route is determined at the intermediate node by comparing the sequenced
numbers with the received destination sequence number. Duplicate copies of RouteRequest
packets having same sequence number are discarded at intermediate node. All intermediate nodes
having the valid routes to the destination are allowed to send the RouteReply packets to the
source.
Figure 1: The (a) RouteReqest and (b) RouteReply message cycles [6].

37
The main advantage of this protocol is that it is a reactive protocol and routes are established on-
demand i.e. whenever source wants to deliver the sensed data to destination then only the path is
established. Sequence numbers are used to find the latest routes to the destination. The
disadvantage is that the intermediate nodes can lead to inconsistent routes if the sequence number
is old. Also periodic beaconing leads to unnecessary bandwidth consumption. Also it does not
repair a broken path locally. The connection setup delay is less, but control overhead is heavy.
This is a reactive protocol which maintains the routing information for a small subset of
destinations, namely for those in use. If there is no route for a new destination, a route discovery
process is invoked, which leads to the significant delays in sensor networks. This limitation
makes this on- demand algorithm less suitable for real-time applications.
2.2. Dynamic Source Routing (DSR) Protocol
DSR [7] protocol is a reactive protocol and another on-demand routing protocol. Unlike AODV,
it is designed to restrict the bandwidth consumed by the control packets in WSNs. It eliminates
the periodic updating of routing tables as it is beacon- less.
Source node broadcasts a RouteRequest packet if it does not have a route for destination and the
packet is further forwarded by each intermediate node if it has not forwarded previously or if it is
not destination node. A Sequence number is carried by each RouteRequest packet generated by
the source node throughout the path it has traversed. Each intermediate node after receiving the
RouteRequest packet checks the sequence number and is forwarded only if it is not a duplicate
RouteRequest with same sequence number. In this way the sequence numbers help in avoiding
loops in routing paths and multiple transmissions of the RouteRequest by an intermediate node.
The destination node receives the RouteRequest packet and replies to the source node through the
reverse path the RouteRequest packet had traversed. Route cache is used which stores all possible
routing information taken from data packet originated from the source node. After receiving a
RouteRequest, if an intermediate node has a route to the destination node in its route cache it
replies to the source node the entire route information from the source node to the destination
node. The source node may receive multiple replies from intermediate nodes, but it selects the
latest and best route. Each data packet carries the complete route information to its destination.
The main advantage of this reactive routing protocol is that there is no need for the update of the
messages. The route cache information in the intermediate nodes efficiently reduces the overhead.
The disadvantage is that it cannot repair broken link locally as the complete path is originated
from the source node. In case of broken link, the source node finds the new route only after
receiving the RouteError from the node adjacent to the broken link. Also route cache information
may result in inconsistent route setup. The connection setup delay is high. Due to the source
routing mechanism, considerable routing overhead is involved which is directly proportional to
the path length. Delay in discovering new routes and considerable connection set up delay makes
this protocol less suitable for real time applications.
2.3. RAP (A Real time communication architecture for large scale wireless sensor
networks)
RAP [8] is the first real-time communication architecture that handles the deadline issues
pertaining to large scale WSNs. It uses the high level query and event services and the velocity
monotonic scheduling (VMS) policy to schedule packets.
RAP provides APIs (Application programming interface) for the applications to address their
queries. This layered architecture ensures that the query is sent to all the nodes in the specified
area, and the responses to the queries are sent back to the base station. The protocol stack of RAP
consists of location addressed protocol (LAP) in the transport layer, Velocity monotonic

38
scheduling (VMS) as the geographic routing protocol, and a contention based MAC scheme to
support prioritization as shown in the Figure 2.
Figure 2: RAP communication architecture model [8]
LAP is a connectionless transport layer protocol. The location based addressing is used for nodes
instead of a unique addressing scheme such as IP address or unique ID for all nodes. The unique
addressing mode is difficult to address the nodes in a sensor network having large number of
nodes. And it supports three kinds of communications mechanisms: unicast, area multicast, and
area anycast. VMS calculates the requested velocity, which takes into consideration the timing
and the distance constraints i.e. it is with this velocity the packet is required to travel towards the
destination. The requested velocity is a measure of the urgency of the packet. If a packet can
travel at its requested velocity, that is, can cover the required distance within a specified time,
then it can meet its deadline. VMS gives high priority to the packets which have higher requested
velocities. Dynamic VMS recalculates the velocity at each intermediate node. This can be
mapped onto a MAC layer priority, handled by the contention-based MAC layer.
Geographic forwarding is used and hence the scalability is possible. One of the performance
metrics of this architecture is mobility. The notation of the velocity is exploited in real-time
communication protocols on sensor networks by this architecture. The key constraints in sensor
networks, namely end-to-end dead line and communication distance are the factors considered in
this protocol. This kind of routing protocol cannot handle long term congestion where diversion
of routing is necessary away from hotspot. The protocol hence provides convenient services for
the application layer programs that require real-time support.
2.4. SPEED (A Stateless Protocol for Real-Time Communication in Sensor
Networks)
SPEED [9] protocol is an important real-time communication protocol to route packets with the
desired speed for sensor networks. This protocol provides the real-time communication services,
such as real-time unicast, real-time area-multicast, real-time area-anycast. These three types of
communication patterns are associated with the type of data delivery. If a part of the network is to
be sensed and needs to be reported to the base station, then it is called as unicast. If it motivates
another type of communication pattern where one end of the route may be an area rather than an
individual node, then it is known as area-multicast. Sometimes it is sufficient to have any node to
respond in an area to avoid redundant information being carried by the nodes in the network. We
can call this routing service as area-anycast. The SPEED is a localized and stateless protocol
which carries minimal control overhead. This protocol is provisioning the efficiency in real-time
communication with the desired speed being maintained across the network for the data packets

39
from source to the destination through a novel combination of feedback control and non-
deterministic QoS aware geographic forwarding.
The SPEED Protocol architecture is shown in the Figure 3. This architecture provides the
combination of MAC and network layer procedures which improves the end-to-end delay
maintaining desired speed throughout the network and provides good response to the congestion
by reducing the traffic near ‘hotspots’ with back pressure rerouting. It consists of the following
components:
• An API( Application Programming Interface)
• A neighbour beacon exchange scheme
• A delay estimator
• The stateless Non-deterministic Geographic forwarding algorithm (SNGF)
• A neighbourhood Feedback loop (NFL)
• Backpressure Rerouting
• Last mile processing
Figure 3: SPEED Protocol [9]
As shown in Figure 3, SNGF is an algorithm used in this protocol to select the suitable neighbour
node that can support the required speed. NFL and Back pressure Rerouting are the two modules
responsible for diverting the traffic when congestion occurs. The last mile process is there to
support the three communication patterns mentioned before. Delay estimator calculates the round
trip single hop delay and newly measured delay is compared with previous delays. In paper [9],
the authors argue that this delay estimation is better metric to represent the congestion than the
average queue size. Beacon exchange provides the geographic location of the neighbour nodes so
that SNGF can do geographic based routing.
This protocol also handles void problems. However, the protocol maintains single speed for
packet delivery throughout the network, which is not suitable for sending various types of data
packets having different deadline. It doesn’t consider the energy metric.
2.5. MMSPEED (Multi-path multi-speed protocol for QoS guarantee of Reliability
& Timeliness in WSN)
MMSPEED [10] extends the SPEED protocol to support different velocities and level of
reliability for multiple probabilistic QoS guarantee in WSNs. The QoS provisioning is performed
in two quality domains, namely timeliness and reliability. Unlike the SPEED, as shown in Figure
4, this protocol provides the multiple network wide options to obtain the QoS in terms of

40
timeliness. For timeliness, this protocol provides multiple layers of network wide speeds
augmented by the two novel techniques: Virtual isolation and dynamic compensation.
Virtual isolation provides the classification of incoming packets according to their speed classes
and places them in appropriate queues, which supports for fast delivery of high-speed packets, not
being affected by the low speed packets. The packets are served in FIFS manner according to the
priority in the queue. For achieving the QoS in terms of reliability, MM-SPEED provides the
probabilistic multipath forwarding. For the prioritized transmission between the nodes, the
network layer has to take support from MAC layer. Hence it uses dynamic compensation which
adjusts the local decisions to meet their end-to-end deadlines. In order to provide the QoS
differentiation in the reliability domain, it provides the multiple redundant paths to the final
destinations, that is, the more the paths to the destination, the higher the probability that the
packet reaches the destination.
Figure 4: Protocol structure at sensor node [10]
This protocol provides the desirable properties such as scalability for large scale networks, self
adaptability to the network dynamics, and works well for both urgent aperiodic and periodic
packets. Many features of MMSPEED may lead to more energy consumption and frames with
large overhead.
2.6. RPAR (Real time Power Aware Routing protocol)
RPAR [11] is the advance version of RAP. It is the only protocol that is designed to support the
real time routing for WSNs with power control. Application specific communication delays are
handled in this protocol by dynamically adapting transmission power and routing decisions based
on the workload and packet deadlines. RPAR uses forwarding policy with power awareness and
neighbourhood manager that efficiently discovers eligible neighbourhood node to forward the
packet in wireless sensor networks. The key feature of this protocol is its adaptability, i.e. for
tight deadlines, it trades energy and capacity to meet the desired time constraints, and for loose
deadlines, it lowers the transmission power to increase the throughput. The protocol architecture
consists of four modules as follows
• Dynamic velocity assignment module, which maps a packet deadline to a required packet
velocity. When a node wants to forward a packet, it uses the velocity assignment module
to calculate the required velocity based on the remaining distance between the present

41
node and the destination node and time to live (TTL). It also prioritizes the packet based
on their deadlines.
• Delay estimator module, which calculates the one- hop delay of different forwarding
choices.
• Forwarding module makes forwarding decisions on packet-by-packet basis. It forwards
the packet to the most energy efficient forwarding choice that meets the required velocity
of the packet.
• Neighbourhood manager effectively handles the neighbourhood table and provides the
best neighbor for forwarding the packets. If there is no information in neighborhood table
about eligible forwarding node then the neighborhood manager is invoked to discover the
forwarding choices with two mechanisms- power adaptation and neighbor discovery. In
the power adaptation scheme, the transmission power is increased to meet the required
velocity for the existing neighbors in the neighborhood table. In neighbor discovery
scheme, new neighbors are discovered that meet the required velocity by sending the
Route to Request (RTR) packets to the neighbors
The proposed power adaption and neighborhood mechanisms are on-demand and hence this
protocol is a reactive protocol. This reactive approach help in discovering neighbors quickly with
low control overhead.This protocol addresses important practical issues like broken links,
scalability and bandwidth constraints. Performance results show that this protocol performs well
in terms of energy consumption and deadline miss ratio.
2.7 THVR (Two-Hop Velocity based routing protocol)
THVR [12] is a two-hop neighbourhood information-based routing protocol for real time wireless
sensor networks proposed to support the QoS in terms of real-time packet delivery along with
better energy efficiency. In this protocol, two-hop information is used to determine the required
velocity and routing decisions are made based on the two-hop velocity with probabilistic packet
dropping mechanism for energy balancing. With the two-hop mechanism, the number of hops
required to transmit the data from source to the destination decreases significantly.
THVR is comprised of four components
• Two-hop velocity based forwarding strategy
• Delay estimation scheme
• Energy- efficient probabilistic drop
• Optimal residual energy cost function for energy balancing.
By the two-hop information, congestion in the network could be predicted at an early time. The
idea of two-hop information provides a trade off between performance and complexity. The
packet deadline is mapped with an adopted velocity as in SPEED. This feature is well suited for
delay constraints. The routing decision is based on the novel two-hop velocity along with the
energy balancing mechanism. The key features of this protocol is that it achieves low deadline
miss ratio along with the high energy efficiency by using novel two hop information based
routing. This real time protocol also considers the efficient energy utilization that has not been
addressed in SPEED and MM-SPEED. By using the two-hop packet delay estimation getting
compared with the required velocity the forwarder node is selected. If suitable forwarder is not
there then the packet is dropped with the probabilistic mechanism. THVR requires more
neighbourhood information for a better decision increasing the complexity cost.

42
2.8 PATH (A Novel Real-Time Power Aware Two-Hop Routing Protocol for
Wireless Sensor Networks)
PATH [13] is a newly proposed real-time protocol which uses the two-hop neighbour information
for routing decisions. The real-time performance is improved by means of reducing the packet
dropping in routing decisions. Dynamic adjustment of transmission power is adopted to reduce
the probability of packet dropping thereby increasing the number of transmission packets that can
meet their deadline. In THVR and SPEED, the main cause of packet dropping is that there is no
eligible forwarding choice in the neighbourhood table for packet forwarding. But PATH provides
the service differentiation and serves different data traffic using dynamic velocity assignment
and control trade-off between energy and delay constraint with dynamic power control. Hence,
packet dropping is reduced with dynamic performance improving the real-time routing in WSNs.
PATH is the integration of power control mechanism with Two-hop Velocity based Routing
(THVR). The key components of this protocol are:
• Forwarding metric and policy, which provides one energy efficient path for
forwarding.
• Power adaptation to discover eligible forwarding choices to avoid packet
dropping.
• Delay estimator estimates the link delay to update the information for the
forwarding policy.
• Initiative drop control module decides whether the packet is to be dropped or not.
It addresses the practical issues like scalability, loss links and network holes. This real time
protocol takes into account the energy consumed and the remaining energy of nodes in the path
from source to destination thereby balancing energy throughout the network effectively.
Performance analysis shows that PATH outperforms THVR in term of dead line miss ratio. Dead
line miss ratio (DMR) is decreased in PATH because packets have more time and more suitable
path to reach destination. THVR energy metric is based only on the remaining energy of the
forwarding candidate but in PATH, it takes into account both remaining energy of the forwarding
candidate and energy that are consumed for sending packet to each forwarding node. So, PATH
uses energy efficiently than THVR.
3. Comparison of Real-Time Routing Protocols
Table 1. Comparison Table of Real-Time Routing Protocols for WSNs
Protocol
Protocol
Operation
Factors Considered
Performance
metrics
Energy
efficiency
Reliability
1 AODV
Demand
driven
End-to-End delay ,
Packet delivery
fraction and Routing
overhead
End-to- End
delay
N/A N/A
2 DSR
Demand
driven
Packet delivery
fraction, end-to-end
delay, Routing
overhead.
Routing
overhead
N/A N/A
3 RAP
Query and
Location
Mobility, Dead line
miss ratio and
End-to-End
deadline miss
N/A N/A

43
Distance constraints ratio
4 SPEED Location
End-to-End delay,
Dead line miss ratio,
Energy
consumption, Void
avoidance
End-to-End
delay, Dead
line miss ratio
Low N/A
5
MM
SPEED
Location
Reliability,
Timeliness,
Scalability
Average
delay,
Overhead,
Reliability
Low Good
6 RPAR Location
Energy
consumption, Dead
line miss Ratio,
Lossy links,
scalability, BW
constraints
Energy
Consumption,
Dead line miss
ratio
Good N/A
7 THVR Location
Energy
consumption,
Deadline miss ratio,
Overhead
Energy
consumption,
Deadline miss
ratio
High Good
8 PATH Location
Energy, Power,
Scalability,
Reliability
Energy
consumption,
Deadline miss
ratio
High Good
4. CONCLUSIONS
Many excellent protocols have been developed for WSN’s. Due to the time constraints, dynamic
node structure, non deterministic nature of the links and resource constrained environment of
WSN, real time routing is quite challenging to meet the requirements of RT systems. In this paper
the review of real time routing protocols along with their key features, their strengths and
weaknesses are presented. The researchers pointed out the various issues like RT, energy aware,
end-to-end delay, deadline miss ratio, reliability, scalability and mobility. From the above
analysis, it is observed that the issues like energy, delay constraints, QoS and reliability are well
addressed. This study reveals that the energy metric is inversely proportional to the time domain
in real time application systems.
REFERENCES
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Abdelzaher, “ Achieving real time target tracking using wireless sensor networks”, in Proc. IEEE
RTAS, pp 37-48, September 2006
[3] D. Malan, T. Fulford Jones, M. Welsh, and S. Moulton, “ An ad hoc sensor network infrastructure for
emergency medical care,” in Proc. Int Workshop Wearable implantable body Sensor networks, April
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[5] C.E. Perkins, E.M. Royer, “ Ad hoc On-Demand Distance Vector Routing,” Proc. of 2nd IEEE
Workshop on Mobile Computing Systems and Applications, New Orleans, LA, February, 1999, pp
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[6] C.E. Perkins, E.M. Royer, “ Multicast operation of the Ad-hoc On-Demand Distance Vector
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[8] C lu, B. M. Blum, T.F.Abdelzaher, J.A. Stankonic and T.He, “ RAP : A real time Architecture for
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Authors
Sandhya Rachamalla is graduated in B.Tech (ECE) from JNTU,Hyd in April, 2004.
She completed M.Tech in Digital Systems and Computer Electronics in June, 2009
from JNT University, Ananthapur. Her areas of interest are Wireless Communications,
Wireless Sensor Networks and Routing Protocols. She has six publications in various
International and National Conferences and Journals. She is presently pursuing Ph.D
from JNTU, Hyderabad and working as an Associate Professor in ECE Department
of Sreenidhi Institute of Science and Technology, Hyderabad. She is an IEEE member.
Dr. K. Anitha Sheela is graduated in B. Tech. (ECE) from REC ,Warangal during
May,1993 and completed ME in Systems and Signal Processing from College of
Engineering, OU, during 1995-1997 and Ph. D from JNTU, Hyderabad during 2003 to
2008. She had worked as Testing Engineer at Onyx Industries for 2 years and has
been in teaching for more than a decade. Now, she is the Additional Controller of
Examinations at JNTUH, Hyderabad, A.P. India. She has 21 papers published in
various National and International Conferences and Journals. Her areas of interest are
Wireless Networks, Speech Processing, Pattern Recognition, Image Processing, DSP
Processors and Neural Networks .She is Fellow of IETE and life member of ISTE. She
is presently working as an Associate Professor in ECE Dept of JNTU, Hyderabad, guiding 5 Ph.D.
scholars .She is Ph. D adjudicator for Sri Satya Sai University, Prasanthi Nilayam.

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