Keivan Ronasi

Delay–Throughput Enhancement in Wireless Networks With Multipath Routing and Channel Coding

Multipath routing and adaptive channel coding are two well-known approaches that have been separately applied to wireless networks to improve the effective throughput. However, it is usually expected that achieving a high throughput would be at a noticeable cost of increasing the average end-to-end delay and causes major degradation in the overall network performance. In this paper, we show that a combination of multipath routing and adaptive channel coding can improve throughput and reduce delay and that it is possible to trade off delay for throughput and vice versa. This is in contrast to the general expectation that higher throughput can only be achieved with noticeable degradations in the end-to-end network delay. In this regard, we jointly formulate the end-to-end data rate allocation and adaptive channel coding (at the physical layer) within the general framework of network utility maximization (NUM). Depending on the choice of the objective function, we formulate two NUM problems: one aiming to maximize the aggregate network utility and another one aiming to maximize the minimum utility among the end-to-end flows to achieve fairness, which is of interest in certain vehicular network applications. Simulation results confirm that we can significantly decrease the average delay at the cost of a small decrease in throughput. This is achieved by maximizing the aggregate utility in the network when fairness is not the dominant concern. Furthermore, we also show that, even when resource allocation is performed to provide fairness, we can still decrease the maximum end-to-end delay of the network at the cost of a slight decrease in the minimum throughput.

Distributed Scheduling in Multihop Wireless Networks with Maxmin Fairness Provisioning

Fair allocation of resources is an important consideration in the design of wireless networks. In this paper, we consider the setting of multihop wireless networks with multiple routing paths and develop an online flow control and scheduling algorithm for packet admission and link activation that achieves high aggregate throughput while providing different data flows with a fair share of network capacity. For fairness provisioning, we seek to maximize the minimum throughput provided to flows in the network. To cope with different degrees of data reliability among the different links in the network, we use different channel code rates as appropriate. While we expect performance improvement using channel coding and multipath routing, the main contribution of our work is a joint treatment of network stability, multipath routing and link-level reliability in meeting the overarching goal of maxmin fairness. We develop a decentralized, and hence practical, scheduling policy that addresses various concerns and demonstrate, via simulations, that it is competitive with respect to an optimal centralized rate allocator. We also evaluate the fairness provisioning under the proposed algorithm and show that channel coding improves the performance of the network significantly. Finally, we show through simulations that the proposed algorithm outperforms a class of existing approaches on fairness provisioning, which are developed based on utility maximization.

Flow Starvation Mitigation for Wireless Mesh Networks

Wireless mesh networks can provide scalable high-speed Internet access at a low cost. Fair channel access among different nodes in the wireless mesh network, however, is an important consideration that needs technological solutions before mesh networks can be widely deployed. Lack of fairness significantly decreases the throughput of nodes that are more than one hop away from mesh gateways. We propose an analytical model and use simulation studies to establish the existence of starvation in mesh networks even when we can ameliorate problems due to exposed terminals. Motivated by the inability of standard medium access control (MAC) protocols to limit starvation, we propose a modification to the MAC protocol to alleviate flow starvation. Our proposed algorithm improves the channel usage of short-term flows with nodes that are multiple hops from the gateway by a factor of 7 in some cases with a penalty of 20% reduction in total throughput across all nodes. Our proposed algorithm also has a better performance than two other schemes in terms of a higher fairness index.

An Enhanced Random-walk Method for Content Locating in P2P Networks

The important problem of content location in an unstructured distributed network (such as P2P, with no central searching system, graph construction control or file placement regulation) is addressed. The existing methods that are based on either flooding or random walk impose a large traffic load on the network or require a long time to search. In this work, we propose a method that outperforms the existing methods in both of these measures. These advantages are achieved by publishing traces of the contents of each node in its nearby nodes, so that the closer nodes to the target have a stronger trace of it. Such traces are used to rapidly locate the desired content. The superb performance of our method, both in time and bandwidth, is demonstrated by simulations whose results are reported.

Reliability-Based Rate Allocation in Wireless Inter-Session Network Coding Systems

Network coding has recently received increasing attention to improve performance and increase capacity in both wired and wireless communication networks. In this paper, we focus on inter-session network coding, where multiple unicast sessions jointly participate in network coding. Wireless links are often unreliable because of varying channel conditions. We consider multi-hop unicast sessions over unreliable links and propose a distributed end-to-end transmission rate adjustment mechanism to maximize the aggregate network utility by taking into account the wireless link reliability information. This includes an elaborate modeling of end-to-end reliability. Simulation results show that by taking into account the reliability information, we can increase the network throughput by up to 100% for some network topologies. We can also increase the aggregate network utility significantly for various choices of utility functions.

Throughput-Efficient Scheduling and Interference Alignment for MIMO Wireless Systems

Multiple-input multiple-output (MIMO) wireless communication systems can achieve higher throughput through interference alignment. For a small number of users, determining the maximum possible degrees of freedom as well as the feasibility of interference alignment in MIMO systems is well studied. However, the issues of scheduling in systems employing interference alignment and serving a large number of users have received little attention so far. In this paper, we study the problem of joint scheduling, interference alignment, and packet admission control in MIMO wireless systems with the goal of maximizing system throughput subject to stability constraints. We formulate a stochastic network optimization problem and propose a scheduling and interference alignment (SIA) algorithm. In each time slot, SIA schedules some users among many competing ones to transmit data, and determines encoding and decoding matrices for the selected users. Packet admission control is performed in each time slot. In addition, we propose a heuristic semi-distributed algorithm (SDSIA), which has a lower computational complexity than the SIA algorithm. Via simulation, we evaluate the performance of SIA and SDSIA for different algorithm parameters and different numbers of users. We also compare the performance of SDSIA with other approaches which do not simultaneously exploit interference alignment and scheduling and find that the combination of these two techniques increases the achievable data rate dramatically.

A multi-sender multicast algorithm for media streaming on peer-to-peer networks

Unlike those on Internet, the media providers on P2P networks are ordinary nodes with limited shared resources such as bandwidth. Multi-sender methods are the best existing solutions to video streaming on P2P networks. In this paper, we propose use of a multicast method on the top of an arbitrary multi-sender method so that all requesting peers receive almost the same expected bit-rate. Experimental results, derived from implementation of the proposed algorithm on Pastry P2P network confirm our claim. Another advantage of our method over the existing methods is its scalability with the number of receivers.

Wavelet-based unbalanced un-equivalent multiple description coding for P2P networks

Almost all existing multi-description coding (MDC) schemes are designed for media streaming over Internet. In this work, a wavelet-based video MDC technique is introduced that fits the criteria of media streaming over peer-to-peer networks. Our proposed method assigns descriptions to the senders due to their characteristic (i.e. bandwidth and availability). In contrast to traditional MDC, different descriptions in the proposed method have different importance in remaking the original media. Our simulation results show considerable improvement of video quality at the receiver (up to 10 dB) as compared to the state-of-the-art.

IPROMISE: Reliable Multi-Sender Algorithm for Peer-to-Peer Networks

Due to the constraints of P2P networks (such as bandwidth limitation) multiple senders should be employed for reliable multimedia streaming. This paper introduces a mathematic approach to select a set of senders among all available senders to provide the most reliable stream for the receiver. This selection is based on upload bandwidths and availability of peers as well as bandwidth of links connecting the senders and the receiver. Our method is called IPROMISE as it is an improved version of the PROMISE algorithm. Simulation results demonstrate improved media quality delivered to the receiver, while the complexity of sender selection remains the same.

Optimal Data Transmission and Channel Code Rate Allocation in Multi-Path Wireless Networks

Wireless links are often unreliable and prone to transmission error due to varying channel conditions. These can degrade the performance in wireless networks, particularly for applications with tight quality-of-service requirements. A common remedy is to use channel coding where the transmitter node adds redundant bits to the transmitted packets in order to reduce the error probability at the receiver. However, this per-link solution can compromise the link data rate, leading to undesired end-to-end performance. In this paper, we show that this latter shortcoming can be mitigated if the end-to-end transmission rates and channel code rates are selected properly over multiple routing paths. We formulate the joint channel coding and end-to-end data rate allocation problem in multipath wireless networks as a network throughput maximization problem, which is non-convex. We tackle the non-convexity by using function approximation and iterative techniques from signomial programming. Simulation results confirm that by using channel coding jointly with multi-path routing, the end-to-end network performance can be improved significantly.