Yigal Bejerano

Fairness and load balancing in wireless LANs using association control

The traffic load of wireless LANs is often unevenly distributed among the access points (APs), which results in unfair bandwidth allocation among users. We argue that the load imbalance and consequent unfair bandwidth allocation can be greatly reduced by intelligent association control. In this paper, we present an efficient solution to determine the user-AP associations for max-min fair bandwidth allocation. We show the strong correlation between fairness and load balancing, which enables us to use load balancing techniques for obtaining optimal max-min fair bandwidth allocation. As this problem is NP-hard, we devise algorithms that achieve constant-factor approximation. In our algorithms, we first compute a fractional association solution, in which users can be associated with multiple APs simultaneously. This solution guarantees the fairest bandwidth allocation in terms of max-min fairness. Then, by utilizing a rounding method, we obtain the integral solution from the fractional solution. We also consider time fairness and present a polynomial-time algorithm for optimal integral solution. We further extend our schemes for the on-line case where users may join and leave dynamically. Our simulations demonstrate that the proposed algorithms achieve close to optimal load balancing (i.e., max-min fairness) and they outperform commonly used heuristics.

Cell Breathing Techniques for Load Balancing in Wireless LANs

Maximizing network throughput while providing fairness is one of the key challenges in wireless LANs (WLANs). This goal is typically achieved when the load of access points (APs) is balanced. Recent studies on operational WLANs, however, have shown that AP load is often substantially uneven. To alleviate such imbalance of load, several load balancing schemes have been proposed. These schemes commonly require proprietary software or hardware at the user side for controlling the user-AP association. In this paper we present a new load balancing technique by controlling the size of WLAN cells (i.e., APs coverage range), which is conceptually similar to cell breathing in cellular networks. The proposed scheme does not require any modification to the users neither the IEEE 802.11 standard. It only requires the ability of dynamically changing the transmission power of the AP beacon messages. We develop a set of polynomial time algorithms that find the optimal beacon power settings which minimize the load of the most congested AP. We also consider the problem of network-wide min-max load balancing. Simulation results show that the performance of the proposed method is comparable with or superior to the best existing association-based methods.

Efficient integration of multihop wireless and wired networks with QoS constraints

This study considers the problem of designing an efficient and low-cost infrastructure for connecting static multihop wireless networks with wired backbone, while ensuring QoS requirements such as bandwidth and delay. This infrastructure is useful for designing low-cost and fast deployed access networks in rural and suburban areas. It may also be used for providing access to sensor networks or for efficient facility placement in wireless networks. In these networks, some nodes are chosen as access points and function as gateways to access a wired backbone. Each access point serves a cluster of its nearby user, and a spanning tree rooted at the access point is used for message delivery. The study addresses both the design optimization and the operation aspects of the system. From the design perspective, we seek for a partition of the network nodes into a minimal number of disjoint clusters that satisfy multiple constraints; each cluster is required to be a connected graph with an upper bound on its radius. We assume that each node has a weight (representing its bandwidth requirement), and the total weight of all cluster nodes is also bounded. We show that these clustering requirements can be formulated as an instance of the capacitated facility location problem (CFLP) with additional constraints. By breaking the problem into two subproblems and solving each one separately, we propose polynomial time approximation algorithms that calculate solutions within a constant factor of the optimal ones. From the operation viewpoint, we introduce an adaptive delivery mechanism that maximizes the throughput of each cluster without violating the QoS constraints.

Physical topology discovery for large multisubnet networks

Knowledge of the up-to-date physical (i.e., layer-2) topology of an Ethernet network is crucial to a number of critical network management tasks, including reactive and proactive resource management, event correlation, and root-cause analysis. Given the dynamic nature of todays IP networks, keeping track of topology information manually is a daunting (if not impossible) task. Thus, effective algorithms for automatically discovering physical network topology are necessary. In this paper, we propose the first complete algorithmic solution for discovering the physical topology of a large, heterogeneous Ethernet network comprising multiple subnets as well as (possibly) dumb or uncooperative network elements. Our algorithms rely on standard SNMP MIB information that is widely supported in modern IP networks and require no modifications to the operating system software running on elements or hosts. Furthermore, we formally demonstrate that our solution is complete for the given MIB data; that is, if the MIB information is sufficient to uniquely identify the network topology then our algorithm is guaranteed to recover it. To the best of our knowledge, ours is the first solution to provide such a strong completeness guarantee.

Efficient load-balancing routing for wireless mesh networks

Wireless mesh networks (WMNs) consist of static wireless routers, some of which, called gateways, are directly connected to the wired infrastructure. User stations are connected to the wired infrastructure via wireless routers. This paper presents a simple and effective management architecture for WMNs, termed configurable access network (CAN). Under this architecture, the control function is separated from the switching function, so that the former is performed by an network operation center (NOC) which is located in the wired infrastructure. The NOC monitors the network topology and user performance requirements, from which it computes a path between each wireless router and a gateway, and allocates fair bandwidth for carrying the associated traffic along the selected route. By performing such functions in the NOC, we offload the network management overhead from wireless routers, and enable the deployment of simple/low-cost wireless routers. Our goal is to maximize the network utilization by balancing the traffic load, while providing fair service and quality of service (QoS) guarantees to the users. Since, this problem is NP-hard, we devise approximation algorithms that provide guarantees on the quality of the approximated solutions against the optimal solutions. The simulations show that the results of our algorithms are very close to the optimal solutions.

Lifetime and coverage guarantees through distributed coordinate-free sensor activation

Wireless Sensor Networks are emerging as a key sensing technology, with diverse military and civilian applications. In these networks, a large number of sensors perform distributed sensing of a target field. Each sensor is a small battery-operated device that can sense events of interest in its sensing range and can communicate with neighboring sensors. A sensor cover is a subset of the set of all sensors such that every point in the target field is in the interior of the sensing ranges of at least

Algorithms for computing QoS paths with restoration

k

Efficient integration of multi-hop wireless and wired networks with QoS constraints

different sensors in the subset, where k is a given positive integer. The lifetime of the network is the time from the point the network starts operation until the set of all sensors with non-zero remaining energy does not constitute a sensor cover. An important goal in sensor networks is to design a schedule, that is, a sequence of sensor covers to activate in every time slot, so as to maximize the lifetime of the network. In this paper, we design a polynomial-time, distributed algorithm for maximizing the lifetime of the network and prove that its lifetime is at most a factor O(log n * log nB) lower than the maximum possible lifetime, where n is the number of sensors and B is an upper bound on the initial energy of each sensor. Our algorithm does not require knowledge of the locations of nodes or directional information, which is difficult to obtain in sensor networks. Each sensor only needs to know the distances between adjacent nodes in its transmission range and their sensing radii. In every slot, the algorithm first assigns a weight to each node that is exponential in the fraction of its initial energy that has been used up so far. Then, in a distributed manner, it finds a O(log n) approximate minimum weight sensor cover which it activates in the slot. Our simulations reveal that our algorithm substantially outperforms several existing lifetime maximization algorithms.

Simple and Efficient k-Coverage Verification without Location Information

There is a growing interest among service providers to offer new services with Quality of Service (QoS) guarantees that are also resilient to failures. Supporting QoS connections requires the existence of a routing mechanism, that computes the QoS paths, i.e., paths that satisfy QoS constraints (e.g., delay or bandwidth). Resilience to failures, on the other hand, is achieved by providing, for each primary QoS path, a set of alternative QoS paths used upon a failure of either a link or a node. The above objectives, coupled with the need to minimize the global use of network resources, imply that the cost of both the primary path and the restoration topology should be a major consideration of the routing process. We undertake a comprehensive study of problems related to finding suitable restoration topologies for QoS paths. We consider both bottleneck QoS constraints, such as bandwidth, and additive QoS constraints, such as delay and jitter. This is the first study to provide a rigorous solution, with proven guarantees, to the combined problem of computing QoS paths with restoration. It turns out that the widely used approach of disjoint primary and restoration paths is not an optimal strategy. Hence, the proposed algorithms construct a restoration topology , i.e., a set of bridges, each bridge protecting a portion of the primary QoS path. This approach guarantees to find a restoration topology with low cost when one exists.

Robust monitoring of link delays and faults in IP networks

This study considers the problem of designing an efficient and low-cost infrastructure for connecting static multihop wireless networks with wired backbone, while ensuring QoS requirements such as bandwidth and delay. This infrastructure is useful for designing low-cost and fast deployed access networks in rural and suburban areas. It may also be used for providing access to sensor networks or for efficient facility placement in wireless networks. In these networks, some nodes are chosen as access points and function as gateways to access a wired backbone. Each access point serves a cluster of its nearby user, and a spanning tree rooted at the access point is used for message delivery. The study addresses both the design optimization and the operation aspects of the system. From the design perspective, we seek for a partition of the network nodes into a minimal number of disjoint clusters that satisfy multiple constraints; each cluster is required to be a connected graph with an upper bound on its radius. We assume that each node has a weight (representing its bandwidth requirement), and the total weight of all cluster nodes is also bounded. We show that these clustering requirements can be formulated as an instance of the capacitated facility location problem (CFLP) with additional constraints. By breaking the problem into two subproblems and solving each one separately, we propose polynomial time approximation algorithms that calculate solutions within a constant factor of the optimal ones. From the operation viewpoint, we introduce an adaptive delivery mechanism that maximizes the throughput of each cluster without violating the QoS constraints.