29-12-2012, 05:51 PM
Improvement in Network Lifetime for On-Demand Routing in Mobile Ad
hoc Networks Using either On-Demand Recharging or Transmission Power Control or Both
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Abstract
Given a fixed energy budget for the operation of a mobile ad hoc network (MANET), on-demand recharging is the
technique of charging the nodes initially with identical, but reduced energy level called the recharge quantum, and then
recharging the nodes with the recharge quantum of energy whenever the energy level at a node goes below a threshold
level. Transmission power control is the technique of adjusting the transmission power at a sender node depending on
the distance to the receiver node. The high-level contribution of this paper is a simulation-based analysis of the network
lifetime obtained for each of the following four scenarios: [a] No power control, No on-demand recharging; Power
control, but no on-demand recharging.
Introduction
A mobile ad hoc network (MANET) is a dynamic distributed system of wireless nodes where in the nodes move
independent of each other. MANETs have several operating constraints such as: limited battery charge per node, limited
transmission range per node and limited bandwidth. Routes in MANETs are often multi-hop in nature. Packet
transmission or reception consumes the battery charge at a node. Nodes forward packets for their peers in addition to
their own. In other words, nodes are forced to expend their battery charge for receiving and transmitting packets that are
not intended for them. Given the limited energy budget for MANETs, inadvertent over usage of the energy resources of
a small set of nodes at the cost of others can have an adverse impact on the node lifetime.
There exist two classes of MANET routing protocols: proactive and reactive. The reactive (also called on-demand)
routing protocols tend to be more economical in terms of energy and bandwidth usage (Broch, Maltz, Johnson, Hu &
Jetcheva, 1998; Johansson, Larsson, Hedman, Mielczarek & Degermark, 1999) in dynamically changing scenarios,
characteristic of MANETs. Hence, in this paper, we restrict ourselves to the class of on-demand routing protocols. We
use three on-demand routing protocols.
On-Demand Recharging
Given a fixed energy budget for the operation of a MANET, the basic idea of on-demand recharging is to charge the
nodes initially with identical, but reduced energy level called the recharge quantum, and then recharge a node only
when it is about to run out of energy. On-demand recharging is basically a dynamic resource allocation strategy for
networks with a common fixed supply of resources whose consumption across the network is unpredictable. A
real-world analogical example would be the case of an investor with a fixed amount of money adjusting his/her
investments in stock market according to the changing trends in the market value of the stocks.
The amount of energy added per recharge operation is called the recharge quantum and under a fixed energy budget, it
is inversely related to the total number of recharges that could be done in the network before a node fails. The smaller
the recharge quantum, the larger is the network lifetime and larger is the percentage of the fixed energy budget usefully
consumed within the network before the time of first node failure. In this paper, in order to determine the maximum
possible improvement in network lifetime, we use a recharge quantum of 1 Joule for every recharge operation. To avoid
any change in performance and unnecessary route transitions, we do not let the energy level of a node to reach zero,
before adding a recharge quantum.
Review of the MANET Routing Protocols
In this section, we provide a brief overview of the minimum-hop based Dynamic Source Routing (DSR) protocol,
stability-based Flow-Oriented Routing Protocol (FORP) and the power-aware Min Max Battery Cost Routing
(MMBCR) algorithm. In this paper, we implemented MMBCR on the top of DSR.
Dynamic Source Routing Protocol
The unique feature of DSR (Johnson, Maltz & Broch, 2001) is source routing: data packets carry information about the
route from the source to the destination in the packet header. As a result, intermediate nodes do not need to store
up-to-date routing information in their forwarding tables. This avoids the need for beacon control neighbor detection
packets that are used in the stability-oriented routing protocols. Route discovery is by means of the broadcast
query-reply cycle. A source node s wishing to send a data packet to a destination d, broadcasts a Route-Request (RREQ)
packet throughout the network. The RREQ packet reaching a node contains the list of intermediate nodes through which
it has propagated from the source node. After receiving the first RREQ packet, the destination node waits for a short
time period for any more RREQ packets, then chooses a path with the minimum hop count and sends a Route-Reply
Packet (RREP) along the selected path. If any RREQ is received along a path whose hop count is lower than the one on
which the RREP was sent, another RREP would be sent on the latest minimum hop path discovered. To minimize the
route acquisition delay, DSR lets intermediate nodes to promiscuously listen to the channel, store the learnt routes (from
the RREQ and data packets) in a route cache and use these cached route information to send the RREP back to the
source. We do not use this feature as promiscuous listening dominates the energy consumed at each node and DSR
could still effectively function without promiscuous listening and route caching. Also, in networks of high node mobility,
cached routes are more likely to become stale, by the time they are used.
Flow-Oriented Routing Protocol (FORP)
FORP (Su & Gerla, 1999) utilizes the mobility and location information of nodes to approximately predict the
expiration time (LET) of a wireless link. The minimum of LET values of all wireless links on a path is termed as the
route expiration time (RET). The route with the maximum RET value is selected. Each node is assumed to be able to
predict the LET values of each of its links with neighboring nodes based on the information regarding the current
position of the nodes, velocity, the direction of movement, and transmission range. FORP assumes the availability of
location-update mechanisms like Global Positioning System (GPS – Hofmann-Wellenhof, Lichtenegger & Collins,
2004) to identify the location of the nodes and also assumes that the clocks across all nodes are synchronized. Route
discovery is similar to the flooding-based query-reply cycle described in Section 3.1, with the information propagated in
the RREQ packet being the predicted LET of each link in a path.
Conclusions and Future Work
The simulation results highlight the improvement in network lifetime obtained with on-demand recharging compared to
transmission power control. Due to the stochastic nature of ad hoc networks and random node movements, many nodes
are lightly used and have abundant energy left at them during the time of first node failure due to exhaustion of the
supplied energy. On-demand recharging actually exploits this unfairness in the routing protocols and attempts to
efficiently use the fixed energy budget by providing energy only at nodes that need energy. With on-demand recharging
(either in the absence or in the presence of power control representing scenarios [c] and [d] respectively), for each of the
routing protocols, we observe that almost the entire fixed energy budget is completely consumed (at least 99.5%) by the
nodes in the network.