Gustavo de Veciana

Dynamic association for load balancing and interference avoidance in multi-cell networks

Next-generation cellular networks will provide higher cell capacity by adopting advanced physical layer techniques and broader bandwidth. Even in such networks, boundary users would suffer from low throughput due to severe intercell interference and unbalanced user distributions among cells, unless additional schemes to mitigate this problem are employed. In this paper, we tackle this problem by jointly optimizing partial frequency reuse and load-balancing schemes in a multicell network. We formulate this problem as a network-wide utility maximization problem and propose optimal offline and practical online algorithms to solve this. Our online algorithm turns out to be a simple mixture of inter- and intra-cell handover mechanisms for existing users and user association control and cell-site selection mechanisms for newly arriving users. A remarkable feature of the proposed algorithm is that it uses a notion of expected throughput as the decision making metric, as opposed to signal strength in conventional systems. Extensive simulations demonstrate that our online algorithm can not only closely approximate network-wide proportional fairness but also provide two types of gain, interference avoidance gain and load balancing gain, which yield 20~100% throughput improvement of boundary users (depending on traffic load distribution), while not penalizing total system throughput.We also demonstrate that this improvement cannot be achieved by conventional systems using universal frequency reuse and signal strength as the decision making metric.

Capacity of ad hoc wireless networks with infrastructure support

We determine the asymptotic scaling for the per user throughput in a large hybrid ad hoc network, i.e., a network with both ad hoc nodes, which communicate with each other via shared wireless links of capacity W bits/s, and infrastructure nodes which in addition are interconnected with each other via high capacity links. Specifically, we consider a network model where ad hoc nodes are randomly spatially distributed and choose to communicate with a random destination. We identify three scaling regimes, depending on the growth of the number of infrastructure nodes, m relative to the number of ad hoc nodes n, and show the asymptotic scaling for the per user throughput as n becomes large. We show that when m /spl lsim/ /spl radic/n/logn the per user throughput is of order W//spl radic/n log n and could be realized by allowing only ad hoc communications, i.e., not deploying the infrastructure nodes at all. Whenever /spl radic/n/log n /spl lsim/ m /spl lsim/ n/log n, the order for the per user throughput is Wm/n and, thus, the total additional bandwidth provided by m infrastructure nodes is effectively shared among ad hoc nodes. Finally, whenever m /spl gsim/ n/log n, the order of the per user throughput is only W/log n, suggesting that further investments in infrastructure nodes will not lead to improvement in throughput. The results are shown through an upper bound which is independent of the routing strategy, and by constructing scenarios showing that the upper bound is asymptotically tight.

Minimizing energy consumption in large-scale sensor networks through distributed data compression and hierarchical aggregation

In this paper, we study how to reduce energy consumption in large-scale sensor networks, which systematically sample a spatio-temporal field. We begin by formulating a distributed compression problem subject to aggregation (energy) costs to a single sink. We show that the optimal solution is greedy and based on ordering sensors according to their aggregation costs-typically related to proximity-and, perhaps surprisingly, it is independent of the distribution of data sources. Next, we consider a simplified hierarchical model for a sensor network including multiple sinks, compressors/aggregation nodes, and sensors. Using a reasonable metric for energy cost, we show that the optimal organization of devices is associated with a Johnson-Mehl tessellation induced by their locations. Drawing on techniques from stochastic geometry, we analyze the energy savings that optimal hierarchies provide relative to previously proposed organizations based on proximity, i.e., associated Voronoi tessellations. Our analysis and simulations show that an optimal organization of aggregation/compression can yield 8%-28% energy savings depending on the compression ratio.

Leveraging dynamic spare capacity in wireless systems to conserve mobile terminals' energy

In this paper, we study several ways in which mobile terminals can backoff on their uplink transmit power in order to extend battery lifetimes. This is particularly effective when a wireless system is underloaded as the degradation in users perceived quality of service can be negligible. The challenge, however, is developing a mechanism that achieves a good tradeoff among transmit power, idling/circuit power, and the performance customers will see. We consider systems with flow-level dynamics supporting either real-time or best effort (e.g., file transfers) sessions. The energy-optimal transmission strategy for real-time sessions is determined by solving a convex optimization. An iterative approach exhibiting superlinear convergence achieves substantial amount energy savings, e.g., more than 50% when the session blocking probability is 0.1% or less. The case of file transfers is more subtle because power backoff changes the system dynamics. We study energy-efficient transmission strategies that realize energy-delay tradeoff. The proposed mechanism achieves a 35%-75% in energy savings depending on the load and file transfer target throughput. A key insight, relative to previous work focusing on static scenarios, is that idling power has a significant impact on energy-efficiency, while circuit power has limited impact as the load increases.

Improving energy efficiency of centrally controlled wireless data networks

Wireless network access protocols can assist nodes to conserve energy by identifying when they can enter low energy states. The goal is to put all nodes not involved in a transmission into the doze state. However, in doing so, one must tradeoff the energy and other costs associated with the overhead of coordinating dozing with the energy savings of putting nodes to sleep. In this paper, we define three alternative directory protocols that may be used by a central node to coordinate the transmission of data and the dozing of nodes. We attempt to optimize their performance by using scheduling and protocol parameter tuning. In addition, we consider the impact of errors and error recovery methods on energy consumption. Although one can argue that carefully scheduling transmissions will improve performance, ultimately, appropriately tuning protocols reduces schedulings significance. In most cases, scheduling transmissions between the same nodes contiguously and ordering such transmissions shortest processing time first results in good performance. The most critical feature that contributes to an access protocols effectiveness is its ability to minimize the time it takes to inform nodes that they may doze. However, the ability of our protocols to conserve energy is highly dependent on (1) network size, (2) traffic type (e.g., down/uplink, and peer-to-peer) and (3) channel bit error rate. In particular, we show that when protocols are faced with packet errors, more elaborate schemes to coordinate the dozing of nodes can pay-off. We conclude by recommending an energy conserving implementation of the IEEE 802.11 Point Coordination Function.

alpha-Optimal User Association and Cell Load Balancing in Wireless Networks

In this paper we develop a framework for user association in infrastructure-based wireless networks, specifically focused on flow-level cell load balancing under spatially inhomogeneous traffic distributions. Our work encompasses several different user association policies: rate-optimal, throughput- optimal, delay-optimal, and load-equalizing, which we collectively denote α-optimal user association. We prove that the optimal load vector ρ∗ that minimizes a generalized system performance function is the fixed point of a certain mapping. Based on this mapping we propose and analyze an iterative distributed user association policy that adapts to spatial traffic loads and converges to a globally optimal allocation.

Spatial energy balancing through proactive multipath routing in wireless multihop networks

In this paper, we investigate the use of proactive multipath routing to achieve energy-efficient operation of ad hoc wireless networks. The focus is on optimizing tradeoffs between the energy cost of spreading traffic and the improved spatial balance of energy burdens. We propose a simple scheme for multipath routing based on spatial relationships among nodes. Then, combining stochastic geometric and queueing models, we develop a continuum model for such networks, permitting an evaluation of different types of scenarios, i.e., with and without energy replenishing and storage capabilities. We propose a parameterized family of energy balancing strategies and study the spatial distributions of energy burdens based on their associated second-order statistics. Our analysis and simulations show the fundamental importance of the tradeoff explored in this paper, and how its optimization depends on the relative values of the energy reserves/storage, replenishing rates, and network load characteristics. For example, one of our results shows that the degree of spreading should roughly scale as the square root of the bits middot meters load offered by a session. Simulation results confirm that proactive multipath routing decreases the probability of energy depletion by orders of magnitude versus that of a shortest path routing scheme when the initial energy reserve is high

Cluster assignment for high-performance embedded VLIW processors

Clustering is an effective method to increase the available parallelism in VLIW datapaths without incurring severe penalties associated with a large number of register file ports. Efficient utilization of a clustered datapath requires careful binding/assignment of operations to clusters. The article proposes a binding algorithm that effectively explores trade-offs between in-cluster operation serialization and delays associated with data transfers between clusters. Extensive experimental evidence is provided showing that the algorithm generates high quality solutions for representative kernels, with up to 33% improvement over a state-of-the-art binding algorithm.

Throughput optimality of delay-driven MaxWeight scheduler for a wireless system with flow dynamics

We consider a wireless downlink shared by a dynamic population of flows. The flows of random size (bits) arrive at the base station at random times, and leave when they have been completely transmitted. The transmission rate supported by the wireless channel of each flow while the flow awaits transmission varies randomly over time and is independent of that of the other flows. The scheduling problem in this context is to select a flow for transmission based on the current system state (e.g., backlogs, wait times, and channel states of the contending flows). It has recently been shown that for such a system, the well-known (backlog-driven) MaxWeight scheduler is not throughput optimal. That is to say, the MaxWeight scheduler will not stabilize a given system even though it is possible to construct a stabilizing scheduler using the various flow- and channel-related statistics. However, in this paper, we show that the delay-driven MaxWeight scheduler is, nevertheless, throughput optimal for such a system. The delay-driven MaxWeight, like its backlog-driven version, does not require any knowledge of the flow- or channel-related statistics.

Enhancing both network and user performance for networks supporting best effort traffic

With a view on improving user-perceived performance on networks supporting best effort flows, e.g., multimedia/data file transfers, we propose a family of bandwidth allocation criteria that depends on the residual work of on-going transfers. Analysis and simulations show that allocating bandwidth in this fashion can significantly improve the user-perceived delay, bit transmission delay, and throughput over traditional approaches, e.g., by 58% on an 80% loaded linear network. A simple implementation based on TCP Reno, exemplifies how one might approach practically realizing such gains. We discuss several other advantages of incorporating such differentiation at the transport level. In particular we make the case that favoring small transfers combined with user impatience or peak rate constraints, both of which are natural mechanisms for users to express the utility of completing transfers, offers a lightweight approach to achieving good overall network goodput and/or utility for best effort networks.