Congestion management through mvcm and congestion control based on mobile agents

1. Proceedings of the International Conference on Emerging Trends in Engineering and Management (ICETEM14)
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CONGESTION MANAGEMENT THROUGH MVCM AND
CONGESTION CONTROL BASED ON MOBILE AGENTS
Reshma Rajan1
, Jeena Kuriakose2
, Vidhya PM3
1, 2, 3
Department of CSE, SNGCE, Kadayiruppu, Kerala, India
ABSTRACT
Contention between several packets trying to use the same link/channel in a network is the major cause for
congestion. When congestion appears, the network will come to a state where a node or link carries so much data that it
may deteriorate network service quality; resulting in queuing delay, frame or data packets loss and the blocking of new
connections. Congestion Management and control in network is a serious problem. Most of the congestion management
mechanisms try to adjust packet injection rate at the source, in response to the explicit congestion Notifications.
Although these mechanisms are effective there are not able to completely manage the heavy load on the network or
having some drawbacks. This paper focus on mechanism referred to as Marking and Validation Congestion Management
(MVCM). It is always better to take care that the congestion does not happen in network than to have to solve the
problem afterwards. So this paper also uses a Mobile Agent based congestion control technique along with MVCM.
Main aim of MVCM is to properly identify the flows responsible for congestion, by using a more refined packet marking
strategy and then performs necessary corrective actions.
Keywords: AODV Routing Protocol, Congestion, Head-Of-Line (HOL), Mobile Agent (MA), Total Congestion Metric
(TCM).
1. INTRODUCTION
Mobile networks are infrastructure-less network. The nodes in the networks are free to move and thus change
the network topology. Packets are send from source node to destination node by forwarding the packets to neighboring
nodes. These packets are forwarded through the channels to and from each node[1]
. Packets arriving at each node will be
buffered and then forwarded. There may chance of congestion when there are many packets injected to the network than
the network can handle. This may cause packet loss and degrading network performance. Obstruction occurs due to the
packet losses and controlling these obstructions in mobile ad-hoc networks are a key problem. It can be reduced by
involving congestion control and management.
Once congestion is detected in a network, and if it remains for long, packets start accumulate at the queues. As a
consequence advancing of packets at the previous nodes are also get delayed. If this condition persists for long time, will
generate Head-of-Line (HOL) blocking phenomenon- Which prevents forwarding of packets to noncongested links. The
result is that the overall network performance will be low[2]
. So we have to apply congestion management mechanisms in
order to reduce injection rate of packets to the flows that are responsible for congestion. When congestion is detected,
packets are marked to warn the source hosts to reduce the flow. In response the source hosts apply some corrective
actions.
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Volume 5, Issue 12, December (2014), pp. 109-115
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We all know that prevention is better than cure, so it is better to avoid the chance of congestion to occur. So
Congestion control mechanisms are needed. Shared wireless channel and dynamic topology of mobile ad-hoc network
increases the chance of congestion. Congestion control mechanisms include routing algorithms and a flow control. In
order to balance the network load and the performance stable, routing nodes load and congestion degree in network is
taken into consideration.
2. BACKGROUND
Fig.1 shows the process of generating congestion in a network
(a) (b)
(c)
Fig.1: generation of congestion process
Fig.1 shows the process of generating congestion in a network. Fig.1(a) shows the initial situation for three
different flows (f1, f2, and f3) crossing the node N. Packets belongs to the flow f1 cross the node from the input channel
IC1 to the output channel OC1. The flow f2 forwards from ICn to OC1, and the flow f3 from ICn to OCn. Suppose the
combined input traffic rate for f1+f2 flows is greater than the bandwidth of the output channel OC1. In such a situation,
packets belonging to the flows f1 and f2 will have to compete for the output channel OC1 and, it may results in the start
of accumulation of packets in the output buffer as shown in Fig.1(b). If the situation remains for long, and f1, f2, f3 flows
are continue being injecting packets into the node, packets may start to accumulate at the input buffer, spreading the
congestion along them[3]
. A possible congestion situation is shown in Fig.1(c). Since the incoming packets are stopped at
the input buffer of the channel ICn, the Head of Line blocking phenomenon appears. This may cause advancing packets
belonging to the flow f3 and addressed towards the noncongested channel OCn. In effect the node as well as the overall
network performance will be degraded. If this situation persists, congestion will be spread along previous nodes, stopping
and accumulating packet at those output buffers.

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3. PROBLEM DISCOVERY AND PROPOSED SYSTEM OVERVIEW
Ad-hoc networks consist of randomly varying network architecture. So adhoc networks require a dynamic
routing protocol that can work with this randomly varying environment. Congestion control[4]
deals with controlling the
incoming traffic to a network. Congestion control and dependability mechanism in association with TCP[5]
is used for
controlling congestion[6]
, and it is not providing information or feedback about the position where congestion occurs. The
drawbacks of a congestion non-adaptive routing protocols is long delay, high overhead and many packet losses[7]
. Packet
loss occurs due to the delay in congestion. This problem can be overcome by using congestion-adaptive routing
protocols-AODV[8].
Ad-hoc On-demand Distance Vector routing (AODV) protocol is a better solution to use for
controlling the packet loss.
Each node in AODV maintains a sequence number[9].
When there is a variation in local connectivity information
of a node, the sequence number is incremented. The fact that the routes are loop-free is promised by these sequence
numbers. A mobile agent based congestion control AODV routing protocol is used here. Some mobile agents inthe
network are collected and these mobile agents aids in selecting the next hop and less loaded neighbor nodes are selected
as next hop.
There can be a possibility for the congestion controlling mechanism to fail. If any congestion appears in the
network, it is necessary to get back the network to its normal performance. So we need efficient congestion management
mechanisms that are able to detect congestion early and to apply appropriate corrective actions that will avoid HOL
blocking and throughput degradation. Current approaches for CMM (Congestion Management Mechanism) do not
guarantee the fact that the corrective actions are carried out on only those packet flows that results congestion.
3.1 Basic strategies applied by current CMMs
Packets provoking congestion are marked by setting 1 bit in the packet header. There are mainly two packet
marking techniques used[10]
.
3.1.1 IPM (Input Packet Marking) Strategy
This strategy is based on marking packets at input buffers. Before packets are stopped and marked, the
congestion tree need to grow at least until reaching the input buffer of the congested node, as shown in Fig1. The
drawback of this strategy is delay. IPM produces a delay, because an output buffer needs to be completely filled before
any input buffer detects congestion. In Fig.1(c), without considering the destination, packets belonging to the flows f2
and f3 are marked. The strategy doesn’t check whether packets are addressed to the congested link OC1 or to non
congested link OCn..Therefore IPM is not much effective because of two drawbacks. First, a delay in detecting
congestion and second an incorrect identification of flows truly causing congestion.
3.1.2 OPM (Output Packet Marking) Strategy
Packets are marked at the output buffer. Consider Fig. 1(b); packets belonging to the flows f1 and f2 are marked
since they are addressed to the congested link OC1. These packets are marked when the output buffer occupancy exceeds
the threshold which is predefined. The contention in this node has been triggered by the flows f1 and f2, those sharing the
congested output link, are responsible for this congestion regardless of their final destination. OPM strategy is not able to
detect whether congestion is affecting other flows which are non responsible for congestion or not. But OPM detects
congestion sooner than IPM.
4. MOBILE AGENT BASED CONGESTION CONTROL AND ROUTING
In mobile agent (MA) based congestion control [11]
,the mobile agents are moves through the network. They
collect and distribute the information about network congestion. They carry routing information and nodes congestion
status within the network.
4.1 Mobile Agent (MA)
Mobile Agent[12]
visits each node in the network. Each node maintains a routing table with k fresh information
records from itself to every other node in the network. Each node id indicated as [S,{(Tci, NHi, ANi, NPi)…..(Tcm, NHm,
ANm, NPm)}] where Tc1 >Tc2 >……>Tm .
m- number of entries and For each i(1 ≤i ≤ m) ,
Tci-time of visiting the adjacent node ANi,
NHi- number of hops
NPi- number of MAs on ANi.
When MA with the history (S,Tc, NH, AN, NP) visits a node N , then the routing information of the node[S,{(Tci, NHi,
ANi, NPi)….(Tcm, NHm, ANm, NPm)}] is updated to[ S;{ ( Tc, NH; AN, NP ),( Tci, NHi, ANi, NPi, NPi)…….( Tcm-1,
NHm-1, ANm-1, NPm-1 ) } ]

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4.2. Total Congestion Metric (TCM)
Mobile agent calculates TCM of each path from source to destination, and selects the path with minimum TCM
value for routing. TCM can be obtained from the estimated queue length and the channel contention.
4.2.1 Queue Length Estimation
The distribution of the queue length PR(Q1), indicates the probability that there are Q1 packets in the queue:
(1)
where Loi represent the offered load at the queue of node i:
(2)
where ARi is aggregate arrival rate of packets produced and forwarded at node i and SRi is the service rate at
node i.
4.2.2 Channel Contention Estimation
Channel occupation due to contention is:
(3)
where,
tRTS= time consumed on Request To Send
tCTS=time consumed on Clear to Send
tSIFS = Short Inter Frame Space(SIFS) period.
Tacc= Time taken due to access contention.
Total congestion metric:
(4)
4.2.3 Architecture
Fig.2: Mobile Agent based congestion control Architectural diagram
This works as follows-
Mobile agent travels to the available one hop neighbors of source S. Then MA selects the shortest path to
destination D. MA1 Moves towards the destination D in a hop-hop manner through the path P1 and MA2 through path
P2. Then MA1 Calculates the total congestion metric TCM1 of path P1, and MA2 calculates that of P2. After calculating
the destination D sends the total congestion metric TCM1 And TCM2 to source S. Source selects path with minimum
value of TCM, that is min(TCM1,TCM2) and sends the packets through that path.

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5. MARKING AND VALIDATION CONGESTION MANAGEMENT MECHANISM
Main aim of Marking and Validation Congestion Management (MVCM)[10]
is to correctly identify the packet
flows that are truly responsible for the congestion in the network and apply the packet injection limitation only at source
nodes that are actually causing congestion.
5.1 Congestion Detection
MVCM mechanism uses a new packet marking strategy by taking the benefits of both Input Packet Marking
strategy and Output Packet Marking strategy; referred as Marking and Validation Packet Marking strategy (MVPM).
MVPM based on the fact that packets are marked at the input buffer and are validated at the output buffers. When the
number of packets in the input buffer exceeds the threshold[13]
, packets arriving to the buffer are marked by setting the
marking bit (MB) in the packet header. When packets are addressed to saturated output link, they are validated by
activating an validation bit (VB) in the packet header. Only marked flows are getting validated.
5.2 Congestion Correction
Two phases of corrective actions are applied in MVCM. These actions are according to the type of flow
classified by MVPM. In the first phase of actions, packet injection rate is reduced by adjusting the dynamic window size.
If congestion persists after window size is fixed to one, then second phase of actions applied, that will reduce even more
the packet injection rate by introducing a waiting interval in between two consecutive packets.
Table 1: Flow classifications and corrective actions
ACK bits
MB VB Types of
flows
Actions
0 0 Cold-flows no actions
1 0 Warm-
flows
Moderate
1 1 Hot-flows Imminent
Cold flows-Flows those are non responsible for congestion.
Hot flows-Flows truly responsible for congestion
Warm flows- flows that are cold flows at the beginning but become hot flows as the congestion spread along the
network.
Moderate Actions-Moderate actions are applied to warm flows. Dynamic window (DW) is modified by reducing its
current value by subtracting one per each marked bit. When window size reaches value equal to one, that is the minimum
value, and then no additional actions are performed. It remains in that stage until a nonmarked ACK packet come. Then
the window size will be increased by one by one.
Imminent Actions - Imminent actions are meant for hot flows. At the beginning this mechanism react by reducing the
window size as moderate actions do. If more and more validated packets are receiving continually, second phase of
actions are applied. Introducing a Waiting Slot (WS) between two consecutive injected packets in such a way that every
received ACK packet with both marking and validation bits set will increase the number of waiting slot.
Window size is initialized according to the minimum RTT (Round Trip Time) of packets. RTTmin= time required by the
data packet to reach destination (tdata) + time required to receive ACK at the origin.( tack) :
(5)
(6)
where
h- no of network hops
thop – routing + switching + link delays.
Ldata–length of data packet
Lack –length of ack packet
B- Channel bandwidth
(7)

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Optimum value of window size will be imposed by the maximum number of packets that can be sent by the
source during the time interval. Window size:
(8)
(9)
where (2* h* t hop *B +Lack ) results in a constant K.So window size can be bounded by the maximum and minimum
allowed data packet sizes:
≤ W ≤
Waiting interval is calculated as follows:
• In the absence of congestion, total number of waiting slots (number_WS) = 0.
• When first ACK with MB and VB bits set arrives, then number_WS =1.
• If more validated ACK received, then number_WS is increased by a constant K..
• Number_WScurrent = K * number_WSprevious assume that WS equal to RTTmin, thenWaiting Interval =
number_WScurrent * RTTmin (10).
5. CONCLUSIONS
In this paper, Mobile Agent based Congestion Control and Marking and Validation Congestion Management
mechanisms are used. Mobile Agents (MA) visits every node in the network, each time when a MA visits a node, it
brings its own history of movements and update the routing table of the node. Total Congestion Metric comprises of
queue length and channel contention of each path, is applied to the routing protocol to select the minimum congested
route in the network. Thus delay and packet loss will be reduced. If any congestion happens then it can be managed by
using Marking and Validation Congestion Management Mechanism. This mechanism is characterized by an effective
packet marking strategy and a fair set of corrective actions. The main advantage of Marking and Validation Packet
Marking strategy is the ability to detect different levels of congestion by classifying the network flows. Further packet
injection limitation is applied with proper intensity according to the level of congestion, thus avoiding the negative
effects over the flows nonresponsible for congestion. As a result recourses are evenly distributed among the network
nodes. Both Congestion Control and Management Mechanisms improve the network throughput and performance.
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