CHAPTER 4 ENERGY AND DELAY AWARE MULTIPATH ROUTING 4.p¢  delay, packet delivery ratio, bandwidth, routing

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    Most of the on-demand routing protocols of MANET uses the

    shortest path method during the path establishment process for data

    transmission and stick to the path till it break. The incessant usage of a single

    path will deplete the battery power. The power failure of a mobile node not

    only affects the node itself but also the overall network lifetime.The mobile

    nodes in the MANET are typically powered by limited energy reservoir.

    Reducing the number of hops will not be the aim of a routing algorithm,

    instead the optimization of multiple parameters such as energy consumption,

    delay, packet delivery ratio, bandwidth, routing overhead, multipath

    establishment etc. Among these issues, decisive issue is constrained energy

    which raises the need of energy efficient routing protocol for MANET. For

    this reason, many research efforts have been devoted to developing energy

    aware routing protocols.

    The delay is the total latency experienced by a packet to traverse the

    network from the source to the destination. At the network layer, the end-to-

    end packet latency is the sum of processing delay, packetization delay,

    transmission delay, queuing delay and propagation delay. The end-to-end

    delay of a path is the summation of the node delay at each node, plus the link

    delay at each link on the path. The end-to-end delay is an additive metric,

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  • 141 because it is the accumulation of all delays of the links along the path. To find

    a QoS feasible path for a concave metric, the available resource on each link

    should be atleast equal to the required value of the metric.

    The high mobility of nodes in MANET causes frequent topological

    changes in the network which may make routes invalid. This in turn leads to

    the frequent route discovery process and high overhead. The multipath routing

    addresses this problem by providing more than one route to a destination node.

    Multipath routing appears to be a promising technique for ad hoc routing

    protocols. The source and intermediate nodes can use these routes as primary

    and backup routes. Alternatively, traffic can be distributed among multiple

    routes to enhance transmission reliability, provide load balancing, and secure

    data transmission. The multipath routing reduces the frequency of route

    discovery effectively and therefore the latency for discovering another route is

    reduced when currently used route is broken. Multiple paths can be useful in

    improving the effective bandwidth of communication, responding to

    congestion and heavy traffic, and in increasing delivery ratio. The

    establishment of multiple paths between source and destination in a single

    route discovery will drastically reduce the frequency of route establishment

    process which in turn increases the overall network performance.

    In addition, metaheuristic algorithms start to emerge as major

    thespians for multi objective global optimization; they often mimic the best

    characteristics in nature, especially biological systems. Many new algorithms

    are emerging with many important applications [25, 29, 39]. Recently, a new

    meta heuristic search algorithm, called BAT algorithm (BA), has been

    developed by Xin-She Yang [56]. Initial studies reveal that the Bat algorithm

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  • 142 is very potential and could outperform existing algorithms. This optimization

    algorithm is applied with the traditional AODV routing protocol for finding

    effective energy and delay aware routing in MANET.

    In this chapter, a novel Energy and Delay aware Dynamic Multipath

    Routing Algorithm using BAT algorithm (BAT-EDMR) is proposed. This

    algorithm modifies and extends AODV to establish dynamic multiple energy

    and delay aware node-disjoint routing paths with the usage of BAT

    optimization technique that provides better packet delivery ratio, minimum

    end-to-end delay and reduced energy consumption and ensures load balancing

    and improved network throughput.

    The remainder of this chapter is organized as follows: Section 4.2

    describes the characteristics of the Bat optimization algorithm. In Section 4.3,

    the mechanism of the proposed novel Energy and Delay Aware Dynamic

    Multipath Routing using BAT Algorithm (BAT-EDMR) is discussed in detail.

    In Section 4.4, the performance of the algorithm BAT-EDMR is analyzed and

    compared with the existing unipath routing protocol AODV and with the

    existing multipath protocol ENDMR. The results are summarised in Section



    BAT algorithm is a recently developed metaheuristic algorithm by

    Xin-She Yang that adopts the behaviour of the natural bats for solving

    optimization problems [56, 57].

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  • 143 4.2.1 Echolocation of Microbats

    Bats are fascinating animals. They are the only mammals with

    wings and they also have advanced capability of echolocation. It is estimated

    that there are about 1000 different species which account for up to about one

    fifth of all mammal species [2]. Their size ranges from the tiny bumblebee bat

    (of about 1.5 to 2 g) to the giant bats with wingspan of about 2 m and weight

    up to about 1 kg. Microbats typically have forearm length of about 2.2 to 11

    cm. Most bats uses echolocation to a certain degree; among all the species,

    microbats are a famous example as microbats use echolocation extensively

    while megabats do not.

    Most microbats are insectivores. Microbats use a type of sonar,

    called, echolocation, to detect prey, avoid obstacles, and locate their roosting

    crevices in the dark. These bats emit a very loud sound pulse and listen for the

    echo that bounces back from the surrounding objects. Their pulses vary in

    properties and can be correlated with their hunting strategies, depending on the


    Most bats use short, frequency-modulated signals to sweep through

    about an octave, while others more often use constant-frequency signals for

    echolocation. Their signal bandwidth varies depends on the species, and often

    increased by using more harmonics.

    Though each pulse only lasts a few thousandths of a second (up to

    about 8 to 10 ms); however, it has a constant frequency which is usually in the

    region of 25 kHz to 150 kHz. The typical range of frequencies for most bat

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  • 144 species are in the region between 25 kHz and 100 kHz, though some species

    can emit higher frequencies up to 150 kHz. Each ultrasonic burst may last

    typically 5 to 20 ms, and microbats emit about 10 to 20 such sound bursts

    every second. When hunting for prey, the rate of pulse emission can be sped

    up to about 200 pulses per second when they fly near their prey. Such short

    sound bursts imply the fantastic ability of the signal processing power of bats.

    In fact, studies show the integration time of the bat ear is typically about 300

    to 400 μs.

    As the speed of sound in air is typically v = 340 m/s, the

    wavelength λ of the ultrasonic sound bursts with a constant frequency f is

    given by λ = v/f, which is in the range of 2 mm to 14 mm for the typical

    frequency range from 25 kHz to 150 kHz. Such wavelengths are in the same

    order of their prey sizes.

    Amazingly, the emitted pulse could be as loud as 110 dB, and,

    fortunately, they are in the ultrasonic region. The loudness also varies from the

    loudest when searching for prey and to a quieter base when homing towards

    the prey. The travelling range of such short pulses is typically a few meters,

    depending on the actual frequencies. Microbats can manage to avoid obstacles

    as small as thin human hairs.

    Studies show that microbats use the time delay from the emission

    and detection of the echo, the time difference between their two ears, and the

    loudness variations of the echoes to build up three dimensional scenario of the

    surrounding. They can detect the distance and orientation of the target, the

    type of prey, and even the moving speed of the prey such as small insects.

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  • 145 Indeed, studies suggested that bats seem to be able to discriminate targets by

    the variations of the Doppler Effect induced by the wing-flutter rates of the