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Modeling Routing Overhead Generated by Wireless Proactive Routing Protocols
Abstract
In this paper, we present a detailed framework consisting of modeling of
routing overhead generated by three widely used proactive routing protocols;
Destination-Sequenced Distance Vector (DSDV), Fish-eye State Routing (FSR) and
Optimized Link State Routing (OLSR). The questions like, how these protocols
differ from each other on the basis of implementing different routing
strategies, how neighbor estimation errors affect broadcast of route requests,
how reduction of broadcast overhead achieves bandwidth, how to cope with the
problem of mobility and density, etc, are attempted to respond. In all of the
above mentioned situations, routing overhead and delay generated by the chosen
protocols can exactly be calculated from our modeled equations. Finally, we
analyze the performance of selected routing protocols using our proposed
framework in NS-2 by considering different performance parameters; Route
REQuest (RREQ) packet generation, End-to-End Delay (E2ED) and Normalized
Routing Load (NRL) with respect to varying rates of mobility and density of
nodes in the underlying wireless network.
... The entire procedure is presented in Eq. (3). [35,34,36]. ...
... It allows nodes to have the most up-to-date information at any given time. Then, Dijkstra's shortest path algorithm is applied to the topology table to select a node from the set of neighboring nodes to forward data packets [49,35]. This mechanism guarantees the detection of the shortest path length between the source node and the sink node. ...
... The FSR protocol is suitable for large mobile networks because it uses the shortest paths for data transmission, and its regional update policy minimizes network traffic. The FSR drawback is the complexity of storing routing tables and processing overhead, and it cannot provide security directly, like most other protocols [35,51]. ...
The Internet of Things (IoT) is a network of various interconnected objects capable of collecting and exchanging data without human interaction. These objects have limited processing power, storage space, memory, bandwidth and energy. Therefore, due to these limitations, data transmission and routing are challenging issues where data collection and analysis methods are essential. The Routing Protocol for Low-power and Lossy Networks (RPL) is one of the best alternatives to ensure routing in LoWPAN6 networks. However, RPL lacks scalability and basically designed for non-dynamic devices. Another drawback of the RPL protocol is the lack of load balancing support, leading to unfair distribution of traffic in the network that may decrease network efficiency. This study proposes a novel RPL-based routing protocol, QFS-RPL, using Q-learning algorithm policy and ideation from the Fisheye State Routing (FSR) protocol. The proposed QFS-RPL is as lightweight and agile as the standardized RPL and partially outperforms the mRPL protocol on mobile networks. This method supports multi-path routing, and at any given time in the network lifetime, all possible paths for sending data from any node to the sink are available. Therefore, QFS-RPL provides high resilience against errors, failures, and sudden network changes. To evaluate the performance of the proposed method, the Contiki operating system and Cooja simulator have been used in scenarios with mobile and stationary nodes and random network topologies. The results have been compared with RPL and mRPL. We have developed an algorithm for ease of data transfer in the IoT, which provides better performance than existing protocols, especially when dealing with a mobile network. The performance evaluation criteria considered for simulation are load balancing, energy consumption, number of table entries, Packet Delivery Ratio (PDR), End-to-End (E2E) latency, network throughput, convergence speed, and control packet overhead.
... In this model, the effect of the capacity of a link along with nonzero constraints is listed for path selection requirement in a link metric. Routing load and routing latency of proactive protocols, pro, are modeled in [13]. To address link metric efficiency in routing protocols, we first construct an integer linear programming model to list the possible constraints against routing overhead. ...
... Equation 1c denotes that there is at most one outgoing link from each node with a nonzero flow. Equations 1a, 1b, and 1c are subjective constraints for a single route in [13]. The links along that path have the same flow, and all other links have zero flow. ...
In this paper, we propose a new Quality Link Metric (QLM), “Inverse Expected Transmission Count
(InvETX),” in Optimized Link State Routing (OLSR) protocol. Then, we compare performance of three existing
QLMs which are based on loss probability measurements: Expected Transmission Count (ETX), Minimum Delay (MD), and Minimum Loss (ML) in Static Wireless Multihop Networks (SWMhNs). A novel contribution of this paper is enhancement in conventional OLSR to achieve high efficiency in terms of optimized routing load and routing latency. For this purpose, first we present a mathematical framework, and then to validate this frame work, we select three performance parameters to simulate default and enhanced versions of OLSR. The three chosen performance parameters are throughput, Normalized Routing Load, and End-to-End Delay. From the simulation results, we conclude that adjusting the frequencies of topological information exchange results in high efficiency.
... FSR uses InterScope and IntraScope [9]. Figure 3 shows the energy cost for IntraScope, (in) , with 2 hops search diameter, and energy cost for 255 hops InterScope, out-sco , respectively. The energy cost of a single packet for FSR ( (FSR) ) is calculated from [22] as (4) OLSR. OLSR (refer to its flow chart in Figure 5) maintains fresh routes via RU Tri throughout the network, and at routing layer LSM Per are sent through HELLO messages. ...
... If the status of MPRs' does not change then default TC interval is used to transmit TC messages (refer to Table 2). The cost of (re)transmissions which are allowed through MPRs is denoted by MPR -nc , and the cost of update messages dissemination throughout the network is denoted by MPR - [22]. Consider ...
... FSR uses InterScope and IntraScope [9]. Figure 3 shows the energy cost for IntraScope, (in) , with 2 hops search diameter, and energy cost for 255 hops InterScope, out-sco , respectively. The energy cost of a single packet for FSR ( (FSR) ) is calculated from [22] as (4) OLSR. OLSR (refer to its flow chart in Figure 5) maintains fresh routes via RU Tri throughout the network, and at routing layer LSM Per are sent through HELLO messages. ...
... If the status of MPRs' does not change then default TC interval is used to transmit TC messages (refer to Table 2). The cost of (re)transmissions which are allowed through MPRs is denoted by MPR -nc , and the cost of update messages dissemination throughout the network is denoted by MPR - [22]. Consider ...
... Many researchers have proposed different protocols to improve the network lifetime and stability region in a WSN. Routing is the backbone of the protocol because the consumption of energy depends upon routing[36]. DR-LEACH[4]was proposed by K.Latif et al..In this technique, the network area is divided into different regions. ...
... We can also use sink mobility to improve the energy utilization efficiency as done in[30,37,38]. In future, we also aim to improve the network energy utilization in the light of wireless ad-hoc networks[29],[30],[33],[34],[35]and[36]. ...
In this paper, we propose Regional Energy Efficient Cluster Heads based on Maximum Energy (REECH-ME) Routing Protocol for Wireless Sensor Networks (WSNs). The main purpose of this protocol is to improve the network lifetime and particularly the stability period of the network. In REECH-ME, the node with the maximum energy in a region becomes Cluster Head (CH) of that region for that particular round and the number of the cluster heads in each round remains the same. Our technique outperforms LEACH [1] which uses probabilistic approach for the selection of CHs. We also implement the Uniform Random Distribution Model to find the packet drop to make this protocol more practical. We also calculate the confidence interval of all our results which helps us to visualize the possible deviation of our graphs from the mean value.
... . (3) Low routing overhead (routing latency and routing load): Routing overhead is discussed in detail in [12] ...
... So, we define this cost in the equation given below to calculate the routing overhead in terms of packet cost. First two costs in eq.10 (eq.10a, 10b) are the same as we have defined in [12]. We define third part (eq.10c) for this work. ...
... Nadeem et.al. [9], enhancing the work of [8], calculate control overhead of FSR, DSDV and OLSR separately in terms of cost of energy as well as cost of time. I.D Aron et.al presents link repairing modeling both in local repairing and source to destination repairing along with comparison of routing protocols in [10]. ...
... Normally there are two types of errors that lead to packet failure and are discussed in detail in [9]. In either case, the probability of packet loss is increased. ...
This paper presents mathematical framework and study of proactive routing
Protocols. The performance analysis of three major proactive routing protocols:
Destination-Sequenced Distance Vector (DSDV), Fish-eye State Routing (FSR) and
Optimized Link State Routing (OLSR) are under consideration in this work.
Taking these routing protocols into account, we enhance existing framework. In
the next step we further discuss and produce analytical framework by
considering variations in different network and protocol parameters. Finally,
experiments are performed regarding above mentioned routing protocols followed
with detailed comparison and analysis of different environments.
... Energy cost for former scope as C (in) E with search diameter of 2 hops, and energy cost for later scope as C out−sco E with number of hops value of 255, respectively is portrayed in Fig. 1. From [12], per packet energy cost for FSR (C ...
... Whereas, TC messages are triggered whenever MPRs' status changes. C MP R E−nc is the cost of allowed (re)transmissions through MPRs, while C MP R E−c shows the cost of dissemination of update messages in the whole network [12]. Fig.1 shows OLSRs HELLO messages are exchanged with their neighbors, and TC messages transmission in entire network only through MPRs. ...
Frequent topological changes due to high mobility is one of the main issues
in Vehicular Ad-hoc NETworks (VANETs). In this paper, we model transmission
probabilities of 802.11p for VANETs and effect of these probabilities on
average transmission time. To evaluate the effect of these probabilities of
VANETs in routing protocols, we select Dynamic Source Routing (DSR), Fish-eye
State Routing (FSR) and Optimized Link State Routing (OLSR). Framework of these
protocols with respect to their packet cost is also presented in this work. A
novel contribution of this work is enhancement of chosen protocols to obtain
efficient behavior. Extensive simulation work is done to prove and compare the
efficiency in terms of high throughput of enhanced versions with default
versions of protocols in NS-2. For this comparison, we choose three performance
metrics; throughput, End-to-End Delay (E2ED) and Normalized Routing Load (NRL)
in different mobilities and scalabilities. Finally, we deduce that enhanced DSR
(DSR-mod) outperforms other protocols by achieving 16% more packet delivery for
all scalabilities and 28% more throughput in selected mobilities than original
version of DSR (DSR-orig).
... Routing overhead is discussed in detail in [12]. ...
... So, we define this cost in the equation given below to calculate the routing overhead in terms of packet cost. First two costs in eq.10 (eq.10a, 10b) are the same as we have defined in [12]. We define third part (eq.10c) for this work. ...
In this paper, we compare and analyze performance of five quality link
metrics forWireless Multi-hop Networks (WMhNs). The metrics are based on loss
probability measurements; ETX, ETT, InvETX, ML and MD, in a distance vector
routing protocol; DSDV. Among these selected metrics, we have implemented ML,
MD, InvETX and ETT in DSDV which are previously implemented with different
protocols; ML, MD, InvETX are implemented with OLSR, while ETT is implemented
in MR-LQSR. For our comparison, we have selected Throughput, Normalized Routing
Load (NRL) and End-to-End Delay (E2ED) as performance parameters. Finally, we
deduce that InvETX due to low computational burden and link asymmetry
measurement outperforms among all metrics.
... A protocol (pro) has to pay some cost C in the form of consumed energy C E and routing delay C T [8]. ...
In this paper, we evaluate and analyze the impact of different network loads and varying no. of nodes on distance vector and link state routing algorithms. We select three well known proactive protocols; Destination Sequenced Distance Vector (DSDV) operates on distance vector routing, while Fish-eye State Routing (FSR) and Optimized Link State Routing (OLSR) protocols are based on link state routing. Further, we evaluate and compare the effects on the performance of protocols by changing the routing strategies of routing algorithms. We also enhance selected protocols to achieve high performance. We take throughput, End-to-End Delay (E2ED) and Normalized Routing Load (NRL) as performance metrics for evaluation and comparison of chosen protocols both with default and enhanced versions. Based upon extensive simulations in NS-2, we compare and discuss performance trade-offs of the protocols, i.e., how a protocol achieves high packet delivery by paying some cost in the form of increased E2ED and/or routing overhead. FSR due to scope routing technique performs well in high data rates, while, OLSR is more scalable in denser networks due to limited retransmissions through Multi-Point Relays (MPRs).
... Further, the addition of NRL in existing schemes show significant improvements in terms of throughput and delay. It is worth mentioning that this study has been conducted by inspiring from [8], [9], [10], [11] and [12]. The comparison of the performance of the selected routing protocols is done by simulating them in NS-2 environment. ...
The contribution of this paper is two fold. It first analyses the flooding strategies for the Wireless Multihop Networks (WMNs) then it enhances the reactive and proactive routing protocols. For analysis purpose, we select four widely used flooding techniques for routing: i. traditional flooding, ii. Time-To-Live based Expanding Ring Search (TTL-based ERS) flooding scheme, iii. TTL-based Scope Routing (SR) flooding and iv. Multi-Point Relays (MPR) flooding. These techniques play a vital role and act as a backbone for routing protocols. Therefore, we compare efficiency of these techniques for six widely used routing protocols: Ad-hoc On-demand Distance Vector (AODV), Destination Sequenced Distance Vector (DSDV), Dynamic Source Routing (DSR), DYnamic MANET On-demand (DYMO), Fish-eye Scope Routing (FSR) and Optimized Link State Routing (OLSR). DSDV uses traditional flooding, AODV, DSR and DYMO use TTL-based ERS flooding, FSR uses TTL-based SR flooding and OLSR uses MPR flooding. This paper also presents mathematical models for flooding techniques and studies the affects of these techniques on their respective protocols in terms of energy and time consumption. This is done to measure the cost incurred by the routing protocols in the form of routing overhead and latencies. A novel contribution of this work is the enhancement in search set values and intervals of routing algorithms to improve the efficiency of selected existing protocols. A detailed comparison analysis of selected protocols with their default and enhanced routing algorithms in NS-2 is also a part of this work.
... From [29], the rate parameter λ (veh/sec) is approximated as, ...
Mobile Ad-hoc NETworks (MANETs) are comprised of wireless mobile nodes that are communicating
with each other without any infrastructure. Vehicular Ad-hoc NETwork (VANET) is
a special type of MANETs in which vehicles with high mobility need to communicate with each
other. In our project, a framework for link availability for static as well as dynamic network and
also experimental parameters in which Packet Delivery Ratio (PDR), effect of link duration over
End-to-End Delay (E2ED) and Normalized Routing Overhead (NRO) in terms of control packets
is analyzed and modeled for MANETs and VANETs. Moreover, this project also contributes the
performance comparison of three reactive routing potocols; Ad-hoc On-Demand Distance Vector
(AODV), DYnamic Source Routing (DSR), DYnamic MANET On-Demand (DYMO) and
three proactive protocols; Destination Sequenced Distance Vector (DSDV), Fish-eye State Routing
(FSR) and Optimized Link State Routing (OLSR). A novel contribution of this work is enhancement
of efficiency of these protocols except DSDV. Three performance parameters; PDR, E2ED
and NRO with varying scalabilities are measured to analyze performance of the selected protocols
both with default and enhanced version. From extensive simulations, it is observed that DSR
outperforms both in MANETs and in VANETs at the cost of delay. Moreover, DSR performs better
in VANETs as compared to MANETs. The NS-2 is used for simulation with TwoRayGround
propagation model. The Simulation of Urban MObility (SUMO) and Vehicular Ad-hoc Networks
Mobility Simulator (VanetMobiSim) are used to generate the mobility pattern for VANETs.
... The authors propose several enhancements in [13] to reduce the stabilization time and thus improve stability in a dynamic environment. In [14], detailed models are presented for rout maintenance operations of some widely used proactive routing protocols. Performance of the selected protocols are then analysed and compared using the proposed model. ...
One of the most important issues in wireless sensor networks (WSNs) is to reduce energy consumption and increase the network lifetime. Proper election of cluster head is one of the approaches to reduce energy consumption in the network. Among existing methods, low-energy adaptive cluster hierarchy (LEACH) is the most prevalent routing algorithm, in which the cluster head is elected based on a given threshold. In LEACH algorithm, only the cluster heads are allowed to send information to the base station (BS). In this paper, a novel routing protocol based on super cluster head election using fuzzy logic in three levels (SCHFTL) is proposed, in which a super cluster head is elected among the cluster heads. The super cluster head election is performed based on a fuzzy description in three levels using Mamdani inference engine. Effectiveness of the proposed SCHFTL routing protocol is verified through MATLAB simulations in terms of death, time of the first node and network lifetime compared with LEACH, cluster head election mechanism using fuzzy logic (CHEF) and fuzzy-based master cluster head election leach (F-MCHEL) protocols.
... Normally there are two types of errors that lead to packet failure as discussed in detail in [30]. ...
... In DSR (refer to its flow chart in Figure 2), searching routes in route cache (RC) of the nodes is known as RCing. [21] the energy cost of RD " (DSR) -RD " is computed as follows: ...
paper presents mathematical framework for calculating transmission probability in IEEE 802.11p based networks at Medium access control (MAC) layer, mathematical framework for calculating energy costs of the chosen routing protocols at network layer, and enhancements in optimized link state routing (OLSR), dynamic source routing, (DSR) and fish-eye state routing (FSR) to tackle delay in vehicular ad hoc networks (VANETs). Besides the enhancements, we analyze ad hoc ondemand distance vector (AODV) along with OLSR, DSR, and FSR as well. To evaluate the effect of our proposed transmission probabilities in the selected routing protocols, we choose network throughput, end-to-end delay (E2ED), and normalized routing load (NRL) as performance metrics. We also investigate the effect of different mobilities as well as scalabilities on the overall efficiency of the enhanced and default versions of the selected protocols. Simulations results which are conducted in NS-2 show that overall DSR-mod outperforms rest of the protocols.
... A detailed framework consisting of modelling the routing overhead generated by three widely used wireless proactive routing protocols; destination-sequenced distance vector (DSDV), fish-eye state routing (FSR) and OLSR is presented in Javaid et al. (2011). In this work, routing overhead of maintenance operations such as plain flooding in DSDV, multipoint relays (MPRs) flooding in OLSR and scope routing of FSR are modelled with respect to appropriate probabilities; the probabilities of changed MPRs, neighbour discovery error and no link breakage. ...
In this paper, we select three most widely used reactive protocols; ad-hoc ondemand
distance vector (AODV), dynamic source routing (DSR) and dynamic manet on-demand (DYMO),
and model their energy and time consumption costs of expanding ring search (ERS) algorithm
in wireless multi-hop networks (WMhNs). A novel contribution of this work is tuning the route
discovery and route maintenance parameters of the chosen protocols to minimise routing overhead.
For analytical comparison, we simulate default and enhanced versions of these protocols using NS-2.
From modeling and analytical comparison, we deduce that adjusting time-to-live (TTL) values in
search sets of ERS algorithm with respective waiting time is more useful for reducing bandwidth
and locating time in chosen protocols. Moreover, for reliable transmission and efficient performance,
reactive protocols need immediate detection of link breakage along with quick repairement strategies
for re-establishment of routes such as local link repair (LLR) and packet salvaging (PS).
... If the status of MPRs' does not change then default TC interval is used to transmit TC messages (refer table 1). The cost of (re)transmissions which are allowed through MPRs is denoted by C M P R E−nc , and the cost of update messages dissemination throughout the network is denoted by C M P R E−c [22]. Low convergence is seen due to delayed updates of routing entries in highly mobile networks. ...
This paper presents mathematical framework for calculating transmission probability in IEEE 802.11p
based networks at Medium Access Control (MAC) layer, mathematical framework for calculating energy
costs of the chosen routing protocols at network layer, and enhancements in Optimized Link State
Routing (OLSR), Dynamic Source Routing (DSR) and Fish-eye State Routing (FSR) to tackle delay in
Vehicular Ad hoc NETworks (VANETs). Besides the enhancements, we analyze Ad-hoc On-Demand
Distance Vector (AODV) along with OLSR, DSR and FSR as well. To evaluate the effect of our proposed
transmission probabilities in the selected routing protocols, we choose network throughput, End-to-End
Delay (E2ED) and Normalized Routing Load (NRL) as performance metrics. We also investigate the
effect of different mobilities as well as scalabilities on the overall efficiency of the enhanced and default
versions of the selected protocols. Simulations results which are conducted in NS-2 show that overall,
DSR-mod outperforms rest of the protocols.
... We aim to introduce multiple QoS parameters [32]. Mobility constraints also help to achieve better network lifetime similar to [33,34]. In future, we also aim to improve the network energy utilization in the light of wireless ad-hoc networks [35], [36], [37], [38], [39] and [40]. ...
In this paper, a novel framework is presented through link and path duration for link availability of paths. Further, we evaluate and analyze our work by varying the number of nodes, pause time and speed in VANETs. We select three routing protocols namely Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Fish-eye State Routing (FSR). Performance of these protocols is analyzed using Packet Delivery Ratio (PDR), Normalized Routing Overhead (NRO), End-to-End Delay (E2ED), Average Link Duration (ALD) and Average Path Duration (APD) against varying scalability, pause time and speed as performance metrices. We perform these simulations with NS-2 implementing Nakagami radio propagation model. The SUMO simulator is used to generate a random mobility pattern for VANETs. To find link duration and path duration we also use MATLAB. From the extensive simulations, we observe that AODV and DSR outperform better among all three routing protocols.
... In [4], Nadeem et al. present a detailed framework consisting of modeling of routing overhead generated by three widely used proactive routing protocols; Destination-Sequenced Distance Vector (DSDV), Fish-eye State Routing (FSR) and Optimized Link State Routing (OLSR). The questions like, how these protocols differ from each other on the basis of implementing different routing strategies, how neighbor estimation errors affect broadcast of route requests, how reduction of broadcast overhead achieves bandwidth, how to cope with the problem of mobility and density, etc, are attempted to respond. ...
... In this model, effect of capacity of a link along with nonzero constraints are listed for path selection requirements in a link metric. Routing load and routing latency of proactive protocols, pro, are modeled in [19]. To address link metric efficiency in routing protocols, we first construct an integer linear programming model to list possible constraints against routing overhead. ...
In this paper, we propose a new Quality Link Metric (QLM), ``Inverse Expected
Transmission Count (InvETX)'' in Optimized Link State Routing (OLSR) protocol.
Then we compare performance of three existing QLMs which are based on loss
probability measurements; Expected Transmission Count (ETX), Minimum Delay
(MD), Minimum Loss (ML) in Static Wireless Multi-hop Networks (SWMhNs). A novel
contribution of this paper is enhancement in conventional OLSR to achieve high
efficiency in terms of optimized routing load and routing latency. For this
purpose, first we present a mathematical framework, and then to validate this
frame work, we select three performance parameters to simulate default and
enhanced versions of OLSR. Three chosen performance parameters are; throughput,
Normalized Routing Load and End-to-End Delay. From simulation results, we
conclude that adjusting the frequencies of topological information exchange
results in high efficiency.
... Packets are dropped due to broken links, change in topology or any radio problem. Normally there are two types of errors that lead to packet failure and are discussed in detail in[9]. In either case, the probability of packet loss is increased. ...
To ensure seamless communication in wireless multi-hop networks, certain
classes of routing protocols are defined. This vary paper, is based upon
proactive routing protocols for Wireless multihop networks. Initially, we
discuss Destination Sequence Distance Vector (DSDV), Fish-eye State Routing
(FSR) and Optimized Link State Routing (OLSR), precisely followed by
mathematical frame work of control overhead regarding proactive natured routing
protocols. Finally, extensive simulations are done using NS 2 respecting above
mentioned routing protocols covering mobility and scalability issues. Said
protocols are compared under mobile and dense environments to conclude our
performance analysis.
... DSDV protocol performs three type of maintenance operations; LSM , RU _per and RU _tri as mentioned in [10]. Whereas, this protocol sends routing messages for RU _tri and RU _per, because of link sensing from MAC layer. ...
Wireless Multi-hop Networks (WMhNs) provide users with the facility to
communicate while moving with whatever the node speed, the node density
and the number of traffic flows they want, without any unwanted delay
and/or disruption. This paper contributes Linear Programming models
(LP_models) for WMhNs. In WMhNs, different routing protocols are used to
facilitate users demand(s). To practically examine constraints of
respective LP_models over different routing techniques, we select three
proactive routing protocols; Destination Sequence Distance Vector
(DSDV), Fish-eye State Routing (FSR) and Optimized Link State Routing
(OLSR). These protocols are simulated in two important scenarios
regarding to user demands; mobilities and different network flows. To
evaluate the performance, we further relate the protocols strategy
effects on respective constraints in selected network scenarios.
... From [14], the rate parameter λ(veh/sec) is approximated as: ...
In this paper, a framework for experimental parameters in which Packet
Delivery Ratio (PDR), effect of link duration over End-to-End Delay (E2ED) and
Normalized Routing Overhead (NRO) in terms of control packets is analyzed and
modeled for Mobile Ad-Hoc NETworks (MANETs) and Vehicular Ad-Hoc NETworks
(VANETs) with the assumption that nodes (vehicles) are sparsely moving in two
different road. Moreover, this paper contributes the performance comparison of
one Proactive Routing Protocol; Destination Sequenced Distance vector (DSDV)
and two reactive protocols; DYnamic Source Routing (DSR) and DYnamic MANET
On-Demand (DYMO). A novel contribution of this work is enhancements in default
versions of selected routing protocols. Three performance parameters; PDR, E2ED
and NRO with varying scalabilities are measured to analyze the performance of
selected routing protocols with their original and enhanced versions. From
extensive simulations, it is observed that DSR outperforms among all three
protocols at the cost of delay. NS-2 simulator is used for simulation with
TwoRayGround propagation model to evaluate analytical results.
... Detailed framework consisting of modeling of routing overhead generated by three widely used proactive routing protocols; DSDV, FSR and OLSR is presented in [7]. ...
In case of high dynamic topology, reactive routing protocols provide quick
convergence by faster route discoveries and route maintenance. Frequent
roadcasts reduce routing efficiency in terms of broadcast cost; Bk, and
expected time cost; E[t]. These costs are optimized using different mechanisms.
So, we select three reactive routing protocols; Ad-hoc On-demand Distance
Vector (AODV), Dynamic Source Routing (DSR), and DYnamic Manet On-demad (DYMO).
We model expanding Ring Search (ERS); an optimization mechanism in the selected
protocols to reduce Bk and E[t]. A novel contribution of this work is
enhancement of default ERS in the protocols to optimize Bk and E[t]. Using
NS-2, we evaluate and compare default-ERS used by these protocols; AODV-ERS1,
DSR-ERS1 and DYMO-ERS1 with enhanced-ERS; AODVERS2, DSR-ERS2 and DYMO-ERS2.
From modeling and analytical comparison, we deduce that by adjusting
Time-To-Live (T TL) value of a network, efficient optimizations of Bk and E[t]
can be achieved.
A mobile ad hoc network is a collection of mobile nodes which communicate without a fixed backbone or centralized infrastructure. Due to the frequent mobility of nodes, routes connecting two distant nodes may change. Therefore, it is not possible to establish a priori fixed paths for message delivery through the network. Because of its importance, routing is the most studied problem in mobile ad hoc networks. In addition, if the Quality of Service (QoS) is demanded, one must guarantee the QoS not only over a single hop but over an entire wireless multi-hop path which may not be a trivial task. In turns, this requires the propagation of QoS information within the network. The key to the support of QoS reporting is QoS routing, which provides path QoS information at each source. To support QoS for real-time traffic one needs to know not only minimum delay on the path to the destination but also the bandwidth available on it. Therefore, throughput, end-to-end delay, and routing overhead are traditional performance metrics used to evaluate the performance of routing protocol. To obtain additional information about the link, most of quality-link metrics are based on calculation of the lost probabilities of links by broadcasting probe packets. In this paper, we address the problem of including multiple routing metrics in existing routing packets that are broadcasted through the network. We evaluate the efficiency of such approach with modified version of DSDV routing protocols in ns-3 simulator. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wireless sensor networks offer many advantages in different application areas with its ease of deployment, low-cost, low-power capabilities. With the increased interest to the wireless sensor networks, the research community have started to carry out network simulations to better analyze the network’s behavior and performance since they provide significant reduction in cost and simulate the different types of sceneries in tolerable time intervals. This chapter introduces the network simulators, i.e., NS-2, OMNET++, J-Sim, OPNET and TOSSIM, respectively with some of the major network programming languages, e.g., nesC and Mate.
This paper presents a new cooperation scheme, i.e. partial cooperation, in MB-OFDM UWB systems for performance enhancement with high throughput and power efficiency. We first take advantage of the available subbands and design an efficient scheme in the time-frequency plane to deliver information bits to the relay node. Then, based on Game Theory, we propose to use hierarchical modulation, which is capable to offer adaptability and flexibilities to attract even a busy relay node that keeps its own communication link participating in cooperation. We also obtain the optimal power allocation coefficients for the proposed partial cooperation scheme. In addition, the optimal constellation priority parameter of hierarchical modulation is also evaluated. Both analytic and simulation results show that the proposed partial cooperation scheme not only achieves performance enhancement but also can upgrade system utilities of both links to get a win-win solution.
One of the major challenges in Wireless Body Area Networks (WBANs) is to
prolong the lifetime of network. Traditional research work focuses on
minimizing transmit power; however, in the case of short range communication
the consumption power in decoding is significantly larger than transmit power.
This paper investigates the minimization of total power consumption by reducing
the decoding power consumption. For achieving a desired Bit Error Rate (BER),
we introduce some fundamental results on the basis of iterative message-passing
algorithms for Low Density Parity Check Code (LDPC). To reduce energy
dissipation in decoder, LDPC based coded communications between sensors are
considered. Moreover, we evaluate the performance of LDPC at different code
rates and introduce Adaptive Iterative Decoding (AID) by exploiting threshold
on the number of iterations for a certain BER (0.0004). In iterative LDPC
decoding, the total energy consumption of network is reduced by 20 to 25%.
In this paper, we simulate the three routing protocols Destination Sequenced Distance Vector (DSDV), Optimized Link state Routing (OLSR), DYnamic MANET On Demand (DYMO) in NS-2 to evaluate and compare their performance using two Mac-layer protocols 802.11 and 802.lip. Comprehensive stimulation work is done for each routing protocol and the performance metrics Throughput, End to End Delay (E2ED), Normalized Routing load (NRL) is analyze in the scenarios of varying the mobilities and scalabilities. After extensive simulations, we observe that DSDV outperforms with 802.1 lp while DYMO gives best performance with 802.11.
Wireless Multi-hop Networks (WMhNs) provide users with the facility to
communicate while moving with whatever the node speed, the node density and the
number of traffic flows they want, without any unwanted delay and/or
disruption. This paper contributes Linear Programming models (LP_models) for
WMhNs. In WMhNs, different routing protocols are used to facilitate users
demand(s). To practically examine the constraints of respective LP_models over
different routing techniques, we select three proactive routing protocols;
Destination Sequence Distance Vector (DSDV), Fish-eye State Routing (FSR) and
Optimized Link State Routing (OLSR). These protocols are simulated in two
important scenarios regarding to user demands; mobilities and different network
flows. To evaluate the performance, we further relate the protocols strategy
effects on respective constraints in selected network scenarios.
In this paper, we evaluate and analyze the impact of different network loads
and varying no. of nodes on distance vector and link state routing algorithms.
We select three well known proactive protocols; Destination Sequenced Distance
Vector (DSDV) operates on distance vector routing, while Fisheye State Routing
(FSR) and Optimized Link State Routing (OLSR) protocols are based on link state
routing. Further, we evaluate and compare the effects on the performance of
protocols by changing the routing strategies of routing algorithms. We also
enhance selected protocols to achieve high performance. We take throughput,
End-to-End Delay (E2ED) and Normalized Routing Load (NRL) as performance
metrics for evaluation and comparison of chosen protocols both with default and
enhanced versions. Based upon extensive simulations in NS-2, we compare and
discuss performance trade-offs of the protocols, i.e., how a protocol achieves
high packet delivery by paying some cost in the form of increased E2ED and/or
routing overhead. FSR due to scope routing technique performs well in high data
rates, while, OLSR is more scalable in denser networks due to limited
retransmissions through Multi-Point Relays (MPRs).
The present note proposes a survey of protocol overheads in mobile ad-hoc networks. An analysis is proposed to estimate overhead due to control packets. An analysis and simulations are proposed to estimate overhead due to non-optimality of the routes constructed by some protocols.
This document describes the Optimized Link State Routing (OLSR)
protocol for mobile ad hoc networks. The protocol is an optimization
of the classical link state algorithm tailored to the requirements of
a mobile wireless LAN. The key concept used in the protocol is that
of multipoint relays (MPRs). MPRs are selected nodes which forward
broadcast messages during the flooding process. This technique
substantially reduces the message overhead as compared to a classical
flooding mechanism, where every node retransmits each message when it
receives the first copy of the message. In OLSR, link state
information is generated only by nodes elected as MPRs. Thus, a
second optimization is achieved by minimizing the number of control
messages flooded in the network. As a third optimization, an MPR
node may chose to report only links between itself and its MPR
selectors. Hence, as contrary to the classic link state algorithm,
partial link state information is distributed in the network. This
information is then used for route calculation. OLSR provides
optimal routes (in terms of number of hops). The protocol is
particularly suitable for large and dense networks as the technique
of MPRs works well in this context.
Many applications, such as disaster response and military applications, call for proactive maintenance of links and routes in Mobile Ad hoc NETworks (MANETs) to ensure low latency during data delivery. The goal of this paper is to minimize the wastage of energy in the network due to high control traffic, which restricts the scalability and applicability of such protocols, without trading-off the low latency. We categorize the proactive protocols based on the periodic route and link maintenance operations performed; and analytically derive the optimum periods for these operations in different protocol classes. The analysis takes into account data traffic intensity, link dynamics, application reliability requirements, and the size of the network. The proposed optimization significantly reduces the control traffic for low data traffic intensity in the network and increases protocol scalability for large networks without compromising the low latency of proactive protocols.
It is well known that neighbor discovery is a critical component of proactive routing protocols in wireless ad hoc networks. However there is no formal study on the performance of proposed neighbor discovery mechanisms. This paper provides a detailed model of key performance metrics of neighbor discovery algorithms, such as node degree and the distribution of the distance to symmetric neighbors. The model accounts for the dynamics of neighbor discovery as well as node density, mobility, radio and interference. The paper demonstrates a method for applying these models to the evaluation of global network metrics. In particular, it describes a model of network connectivity. Validation of the models shows that the degree estimate agrees, within 5% error, with simulations for the considered scenarios. The work presented in this paper serves as a basis for the performance evaluation of remaining performance metrics of routing protocols, vital for large scale deployment of ad-hoc networks.
In this paper, we have modeled the routing over- head generated by three
reactive routing protocols; Ad-hoc On-demand Distance Vector (AODV), Dynamic
Source Routing (DSR) and DYnamic MANET On-deman (DYMO). Routing performed by
reactive protocols consists of two phases; route discovery and route
maintenance. Total cost paid by a protocol for efficient routing is sum of the
cost paid in the form of energy consumed and time spent. These protocols
majorly focus on the optimization performed by expanding ring search algorithm
to control the flooding generated by the mechanism of blind flooding. So, we
have modeled the energy consumed and time spent per packet both for route
discovery and route maintenance. The proposed framework is evaluated in NS-2 to
compare performance of the chosen routing protocols.
Simulation studies have been the predominant method of evaluating ad hoc routing algorithms. Despite their wide use and merits, simulations are generally time consuming. Furthermore, several prominent ad hoc simulations report inconsistent and unrepeatable results. We, therefore, argue that simulation-based evaluation of ad hoc routing protocols should be complemented with mathematical verification and comparison. In this paper, we propose a performance evaluation framework that can be used to model two key performance metrics of an ad hoc routing algorithm, namely, routing overhead and route optimality. We also evaluate derivatives of the two metrics, namely, total energy consumption and route discovery latency. Using the proposed framework, we evaluate the performance of four prominent ad hoc routing algorithms: DSDV, DSR, AODV-LL, and Gossiping. We show that the modeled metrics not only allow unbiased performance comparison but also provide interesting insight about the impact of different parameters on the behavior of these protocols.
In this paper we introduce a new model for ad hoc networks. Our model aims at reproducing the states alternation of links and nodes led by dynamic and random topology of ad hoc networks as well as random delays of packets delivery. Furthermore, we study the phenomenon of uncertainties in routing operation due to the unpredictable topological changes. Unlike mobility models which reflect only the impact of mobility on routing protocols, our proposal can demonstrates the impact of several identified hazards on the performances of proactive routing protocols. We show through various simulations the performances of our model within the framework of a proactive routing.
An ad-hoc network is the cooperative engagement of a collection of Mobile Hosts without the required intervention of any centralized Access Point. In this paper we present an innovative design for the operation of such ad-hoc networks. The basic idea of the design is to operate each Mobile Host as a specialized router, which periodically advertises its view of the interconnection topology with other Mobile Hosts within the network. This amounts to a new sort of routing protocol. We have investigated modifications to the basic BellmanFord routing mechanisms, as specified by the Routing Information Protocol, making it suitable for a dynamic and self-starting network mechanism as is required by users wishing to utilize ad-hoc networks. Our modifications address some of the previous objections to the use of Bellman-Ford, related to the poor looping properties of such algorithms in the face of broken links and the resulting time dependent nature of the interconnection topology describing th...
: In this paper we discuss the mechanism of multipoint relays (MPRs) to e ciently do the ooding of broadcast messages in the mobile wireless networks. Multipoint relaying is a technique to reduce the number of redundant retransmissions while di using a broadcast message in the network. We discuss the principle and the functioning of MPRs, and propose a heuristic to select these MPRs in a mobile wireless environment. We also analyze the complexity of this heuristic and prove that the computation of a multipoint relay set with minimal size is NP-complete. Finally, we present some simulation results to show the e ciency of multipoint relays. Key-words: multipoint relays, mobile wireless networks, ooding of broadcast messages (Rsum : tsvp) Email: Amir.Qayyum@inria.fr, Laurent.Viennot@inria.fr, Anis.Laouiti@inria.fr Unite de recherche INRIA Rocquencourt Domaine de Voluceau, Rocquencourt, BP 105, 78153 LE CHESNAY Cedex (France) Telephone : 01 39 63 55 11 - International : 33 1 39 ...
An ad hoc network is a collection of wireless mobile nodes dynamically forming a temporary network without the use of any existing network infrastructure or centralized administration. Due to the limited transmission range of wireless network interfaces, multiple network "hops" may be needed for one node to exchange data with another across the network. In recent years, a variety of new routing protocols targeted specifically at this environment have been developed, but little performance information on each protocol and no realistic performance comparison between them is available. This paper presents the results of a detailed packet-level simulation comparing four multi-hop wireless ad hoc network routing protocols that cover a range of design choices: DSDV, TORA, DSR, and AODV. We have extended the ns-2 network simulator to accurately model the MAC and physical-layer behavior of the IEEE 802.11 wireless LAN standard, including a realistic wireless transmission channel model, and present the results of simulations of networks of 50 mobile nodes.
Energy consumption is a major issue in designing protocols for ad hoc wireless networks due to battery constrains. This paper identifies the inefficient elements of expanding ring search protocol and proposes the new blocking expanding ring search approach which demonstrates substantial energy savings without an increase in route discovery latency
Bio-inspired ad hoc routing is an active area of research. The designers of these algorithms predominantly evaluate the performance of their protocols with the help of simula- tion studies. Such studies are mostly scenario and simula- tor specific and their results cannot be generalized to other scenarios and simulators. Therefore, we argue that math- ematical tools should be utilized to develop a consistent, provable and compatible formal framework in order to pro- vide an unbiased evaluation of Bio-inspired ad hoc routing protocols. Motivated by this requirement, in this paper, we develop a probabilistic performance evaluation framework that can be used to model the following key performance metrics of an ad hoc routing algorithm: (1) routing over- head, (2) route optimality, and (3) energy consumption. We utilize this framework to model a well known Bee-inspired routing protocol for ad hoc sensor networks, BeeSensor. We also show that the proposed framework is generic enough and can easily be adapted to even model a classical rout- ing protocol, Ad Hoc on Demand Distance Vector (AODV). The modeled metrics of the two algorithms not only allow unbiased performance comparison but also provide interest- ing insights into the parameters governing the behavior of these routing protocols.
In this paper, we identify and analyze the requirements to design a new
routing link metric for wireless multihop networks. Considering these
requirements, when a link metric is proposed, then both the design and
implementation of the link metric with a routing protocol become easy.
Secondly, the underlying network issues can easily be tackled. Thirdly, an
appreciable performance of the network is guaranteed. Along with the existing
implementation of three link metrics Expected Transmission Count (ETX), Minimum
Delay (MD), and Minimum Loss (ML), we implement inverse ETX; invETX with
Optimized Link State Routing (OLSR) using NS-2.34. The simulation results show
that how the computational burden of a metric degrades the performance of the
respective protocol and how a metric has to trade-off between different
performance parameters.
In this paper, we propose a new quality link metric, interference and bandwidth adjusted ETX (IBETX) for wireless multi-hop networks. As MAC layer affects the link performance and consequently the route quality, the metric therefore, tackles the issue by achieving twofold MAC-awareness. Firstly, interference is calculated using cross-layered approach by sending probes to MAC layer. Secondly, the nominal bit rate information is provided to all nodes in the same contention domain by considering the bandwidth sharing mechanism of 802.11. Like ETX, our metric also calculates link delivery ratios that directly affect throughput and selects those routes that bypass dense regions in the network. Simulation results by NS-2 show that IBETX gives 19% higher throughput than ETX and 10% higher than Expected Throughput (ETP). Our metric also succeeds to reduce average end-to-end delay up to 16% less than Expected Link Performance (ELP) and 24% less than ETX.
Many wireless ad hoc routing protocols have been proposed in the literature. Researchers are comparing and improving these protocols before standard routing protocols are defined. In this paper, we present a framework for wireless ad hoc routing protocols based on the concept of a relay node set (RNS). This framework facilitates the comparison, design, and improvement of wireless ad hoc routing protocols. We briefly present an analytical model for comparing protocols using this framework with packet overhead as the metric. We also apply the framework to show how to improve a routing protocol. Future work using the framework is also discussed.
: The present note proposes a survey of protocol overheads in mobile ad-hoc networks. An analysis is proposed to estimate overhead due to control packets. An analysis and simulations are proposed to estimate overhead due to non-optimality of the routes constructed by some protocols. Key-words: wireless network, ad-hoc, overhead, ooding, hello (Rsum : tsvp) Email: Philippe.Jacquet@inria.fr y Email: Laurent.Viennot@inria.fr Unite de recherche INRIA Rocquencourt Domaine de Voluceau, Rocquencourt, BP 105, 78153 LE CHESNAY Cedex (France) Telephone : 01 39 63 55 11 - International : +33 1 39 63 55 11 Telecopie : (33) 01 39 63 53 30 - International : +33 1 39 63 53 30 Overhead dans les protocoles de rseaux sans l ad-hoc Rsum : Plusieurs protocoles de routages sont proposs pour les rseaux sans l ad-hoc (sans infrastructure). Pour les comparer, nous proposons une analyse de la surcharge de trac apporte par les protocoles eux-mmes. Une synthse sur les dirents protocoles existan...