Partha P. Bhattacharya

Enhancing throughput over wireless LANs using channel state dependent packet scheduling

Unlike wired networks, packets transmitted on wireless channels are often subject to burst errors which cause back to back packet losses. Most wireless LAN link layer protocols recover from packet losses by retransmitting lost segments. When the wireless channel is in a burst error state, most retransmission attempts fail thereby causing poor utilization of the wireless channel. Furthermore, in the event of multiple sessions sharing a wireless link, FIFO packet scheduling can cause the HOL blocking effect, resulting in unfair sharing of the bandwidth. This observation leads to a new class of packet dispatching methods which explicitly take the wireless channel characteristics into consideration in making packet dispatching decisions. We compare a variety of channel state dependent packet (CSDP) scheduling methods with a view towards enhancing the performance of the transport layer sessions. Our results indicate that by employing a CSDP scheduler at the wireless LAN device driver level, significant improvement in the channel utilization can be achieved in typical wireless LAN configurations.

Using channel state dependent packet scheduling to improve TCP throughput over wireless LANs

In recent years, a variety of mobile computers equipped with wireless communication devices have become popular. These computers use applications and protocols, originally developed for wired desktop hosts, to communicate over wireless channels. Unlike wired networks, packets transmitted on wireless channels are often subject to burst errors which cause back to back packet losses. In this paper we study the effect of burst packet errors and error recovery mechanisms employed in wireless MAC protocols on the performance of transport protocols such as TCP. Most wireless LAN link layer protocols recover from packet losses by retransmitting lost segments. When the wireless channel is in a burst error state, most retransmission attempts fail, thereby causing poor utilization of the wireless channel. Furthermore, in the event of multiple sessions sharing a wireless link, FIFO packet scheduling can cause the HOL blocking effect, resulting in unfair sharing of the bandwidth. This observation leads to a new class of packet dispatching methods which explicitly take wireless channel characteristics into consideration in making packet dispatching decisions. We compare a variety of channel state dependent packet (CSDP) scheduling methods with a view towards enhancing the performance of transport layer sessions. Our results indicate that by employing a CSDP scheduler at the wireless LAN device driver level, significant improvement in channel utilization can be achieved in typical wireless LAN configurations.

Optimal scheduling with strict deadlines

The problem of dynamic scheduling of customers (messages) in time-critical environments is discussed. A single station (communication node) is considered, and it is assumed that each customer (message) must begin service (transmission) by an individually varying extinction time or else it is lost. Interest is in minimizing, in the sense of stochastic order, the number of messages lost over any time interval. A variety of results is proved that establishes the optimality of the shortest-time-to-extinction policy under rather general conditions. Similar results are found when messages have constraints on their complete transmission times. A network of M stations in tandem is considered under the hypothesis that a message is never lost and is scheduled irrespective of whether its extinction time (also called due date in this case) has expired or not. Under fairly general assumptions on the arrivals, deadlines, and services, it is shown that the earliest-due-date policy minimizes a form of average tardiness incurred over a finite operating horizon among all non-idling nonpreemptive policies. These problems are formulated in the context of stochastic dominance, and simple interchange arguments are used to establish all results. >

Allocation of interdependent resources for maximal throughput

A general queueing network model of computer and communication systems with interdependent resources is considered. The resources are modeled by a collection of servers that have to be allocated subject to certain constraints. Arrivals are Poisson, services are independent and identically distributed and service completions of different customers cannot be synchronized. A set of necessary conditions for the finiteness of long run average delays is obtained. An adaptive non-preemptive scheduling policy is presented and a set of sufficient conditions under which the policy achieves finite delays, is identified. The necessary and sufficient conditions differ only on the boundary region. The policy does not depend on the knowledge of the arrival rates and has polynomial time complexity for some applications

An architecture and implementation toward multiprotocol mobility

The challenge is to design a set of protocols that provide seamless and robust network connectivity to mobile users for a variety of existing network protocol suites. An important additional constraint is that the design should not require any changes to the existing stationary infrastructure and it should interoperate with the existing protocol stacks at the stationary hosts. We propose a mobile data link (MDL) architecture that endeavors to meet this design challenge. The architecture hides the topological effects of mobility at the data link layer, thus making topology changes due to mobility transparent at layers above the data link. This provides a single mechanism to support a variety of distributed applications that use different protocol stacks without requiring changes to the implementations of the stacks. Further, the-solution provides the enhanced degree of mobility provided by prior network layer solutions. The novel features of the proposed solution are the use of the network layer infrastructure for carrying data link traffic, the ability to dynamically maintain a data link overlay over a common network layer infrastructure, and efficient handling of the broadcast traffic. We have developed an MDL architecture that allows data link networks (formed by the interconnection of LAN segments by bridges) to be dynamic, thereby supporting mobile hosts, eliminating the need for manual configuration. Moreover, our scheme efficiently handles broadcasts and multicasts. >

Problems of adaptive optimization in multiclass M/GI/1 queues with Bernoulli feedback

Adaptive algorithms are obtained for the solution of separable optimization problems in multiclass M/GI/1 queues with Bernoulli feedback. Optimality of the algorithms is established by modifying and extending methods of stochastic approximation. These algorithms, can be used as a basis for designing policies for semi-separable and approximate lexicographic optimization problems and in the case of M/GI/1 queues without feedback, they also provide a simple policy for lexicographic optimization. The results obtained on stochastic approximation imply convergence of classical recursions such as Robbins-Monroe in cases where the conditional second moment of their increments is not finite.

Optimal allocation of a server between two queues with due times

Two queues share a single server. Arrivals to each queue have individual target due times for service completion (their due times are known to the controller) and a penalty is incurred when they stay in the system after the expiration of these due times. The two classes have different service requirements and incur penalty at different rates. The problem of dynamic priority assignment so as to minimize the discounted and average tardiness per customer is considered. The problem is formulated in discrete time where it is shown that, under the assumptions of geometric arrivals and geometric services, there is a nonidling stationary optimal preemptive policy. Within each class, the policy chooses, if at all, the customer with the smallest due time. A partial order on the space of the set of residual times is introduced. It is shown that the optimal choice of the customer class is monotonic with respect to this partial order; this implies a switchover-type property in the appropriate space. A combination of stochastic dominance and dynamic programming ideas is used to establish the results. >

Adaptive lexicographic optimization in multi-class M/GI /1 queues

We consider a multi-class M/GI/1 system, in which an average response time objective is associated with each class. The performance of each class is measured by the ratio of the average response time over the corresponding value of the objective. To achieve fairness in service allocation it is required to find a policy that lexicographically minimizes the vector of performance ratios arranged in nonincreasing order. We provide such a policy that is adaptive, uses only knowledge of arrival and departure instants, and is thus easy to implement. We also consider a variant of this policy which adapts faster to changes in the statistical parameters of the model. Both policies are analyzed via associated stochastic recursions using techniques of stochastic approximation.

Optimal scheduling with deadline constraints in tree networks

The problem of scheduling time-critical messages over a tree network is considered. Messages arrive at any of the nodes and have to reach the root node before their deadlines expire, else they are considered lost. The network is assumed to be operating in discrete time and the messages need one time unit for transmission from one node to the next along its path. The arrival and deadline processes are arbitrary. The policy which transmits messages with smallest extinction (arrival+deadline) time at every link is shown to minimize the number of lost messages over all time intervals and for every sample path.

Optimality and finite time behavior of an adaptive multiobjective scheduling algorithm

A multiclass M/GI/1 system is considered in which an average response time objective is associated with each class. The performance of each class is measured by the ratio of the average response time over the corresponding value of the objective. To achieve fairness in service allocation it is necessary to find a policy that lexicographically minimizes the vector of performance ratios arranged in nonincreasing order. An adaptive policy is provided that uses only knowledge of arrival and departure instants and is easy to implement. Also considered is a variant of this policy which adapts faster to changes in the statistical parameters of the model. Both policies are analyzed via associated stochastic recursions using techniques of stochastic approximation.<<ETX>>