We analyze the delay performance of a multi-hop wireless network in which the routes between source-destination pairs are fixed. We develop a new queue grouping technique to handle the complex correlations of the service process resulting from the multi-hop nature of the flows and their mutual sharing of the wireless medium. A general set based interference model is assumed that imposes constraints on links that can be served simultaneously at any given time. These interference constraints are used to obtain a fundamental lower bound on the delay performance of any scheduling policy for the system.
We present a systematic methodology to derive such lower bounds. For a special wireless system, namely the clique, we design a policy that is sample path delay optimal. For the tandem queue network, where the delay optimal policy is known, the expected delay of the optimal policy numerically coincides with the lower bound. The lower bound analysis provides useful insights into the design and analysis of optimal or nearly optimal scheduling policies.
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EXISTING SYSTEM:
A large number of studies on multi-hop wireless networks have been devoted to system stability while maximizing metrics like throughput or utility. These metrics measure the performance of a system over a long time-scale. The delay performance of wireless networks, however, has largely been an open problem. This problem is notoriously difficult even in the context of wire line networks, primarily because of the complex interactions in the network (e.g., superposition, routing, departure, etc.) The problem is further exacerbated by the mutual interference inherent in wireless networks which, complicates both the scheduling mechanisms and their analysis.
Disadvantages:
1. Simultaneity
2. Throughput
3. Resource allocation
PROPOSED SYSTEM:
We analyze a multi-hop wireless network with multiple source-destination pairs, given routing and traffic information. Each source injects packets in the network, which traverses through the network until it reaches the destination. A packet is queued at each node in its path where it waits for an opportunity to be transmitted. The delay performance of any scheduling policy is primarily limited by the interference, which causes many bottlenecks to be formed in the network. We develop new analytical techniques that focus on the queuing due to the (K, X)-bottlenecks. One of the techniques, which we call the “reduction technique”, simplifies the analysis of the queuing upstream of a (K, X)-bottleneck to the study of a single queue system with K servers.
Advantages:
1. Single Queue System
2. Back Pressure Policy
3. Saving s of time
MODULES:
1. Characteristics of Bottlenecks
2. Reduction Technique
3. Reduced System
4. Bound on expected delay
5. Design of delay efficient policies
1. Characteristics of bottlenecks in the system
Link interference causes certain bottlenecks to be formed in
the system. We define a (K, X)-bottleneck to be a set of links
X ⊂ L such that no more than K of its links can be scheduled
Simultaneously.
2. Reduction Technique
We describe our methodology to derive lower bounds on the average size of the queues corresponding to the flows that pass through a (K, X)-bottleneck.
3. Reduced System
Consider a system with a single server and AX(t) as the input. The server serves at most K packets from the queue. Let QX(t) be the queue length of this system at time t. Flows II, IV and VI pass through an exclusive set using two, three and two hops of the exclusive set respectively. The corresponding G/D/1 system is fed by the exogenous arrival streams 2AII (t), 3AIV (t) and 2AV I (t).
4. Bound on Expected Delay
We now present a lower bound on the expected delay of the flows passing through the bottleneck as a simple function of the expected delay of the reduced system. In the analysis, we use above Theorem to bound the queuing upstream of the bottleneck and a simple bound on the queueing downstream of the bottleneck. Applying Little’s law on the complete system, we derive a lower bound on the expected delay of the flows passing through the bottleneck.
5. Design of delay efficient policies
A scheduler must satisfy the following properties.
• Ensure high throughput: This is important because if the scheduling policy does not guarantee high throughput then the delay may become infinite under heavy loading.
• Allocate resources equitably: The network resources must be shared among the flows so as not to starve some of the flows. Also, non-interfering links in the network have to be scheduled such that certain links are not starved for service. Starvation leads to an increase in the average delay in the system.
CONCLUSION:
Thus, new approaches are required to address the delay problem in multi-hop wireless systems. To this end, we develop a new approach to reduce the bottlenecks in a multi-hop wireless to single queue systems to
Carry out lower bound analysis.
The analysis is very general and admits a large class of arrival processes. Also, the analysis can be readily extended to handle channel variations. The main difficulty however is in identifying the bottlenecks in the system. The lower bound not only helps us identify near-optimal policies, but may also help in the design of a delay-efficient policy
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