Amir A. Sayegh

The need for access point power saving in solar powered WLAN mesh networks

Wireless LAN mesh networks are now being used to deploy Wi-Fi coverage in a wide variety of outdoor applications. In these types of networks, conventional WLAN mesh nodes must be operated using continuous electrical power connections. This requirement may often be very expensive, especially when the network includes expansive outdoor wireless coverage areas. An alternative is to operate some of the WLAN mesh nodes using an energy sustainable source such as solar or wind power. This eliminates the need for a fixed power connection, making the node truly tetherless and allowing more flexibility in node positioning. In this article we first review the background and recent activities in the area of energy sustainable WLAN mesh networks. These types of networks are provisioned geographically, in that the assigned resources are a function of the geographic region where the network is to be deployed. The theory behind this is briefly described using some sample North American locations. We then discuss the current shortcomings of IEEE 802.1 1 when used in these types of networks. IEEE 802.11 requires that the access point be continuously powered, and this requirement is a major barrier to deploying cost-effective sustainable energy networks in certain applications. Recent work is then reviewed that has begun to address the changes that would be required to the standard to better support these types of networks.

Energy Provisioning in Solar-Powered Wireless Mesh Networks

Solar-powered wireless mesh nodes must be provisioned with a solar panel and battery combination that is sufficient to prevent node outage. This is normally done using historical solar insolation data for the desired deployment location and based on a temporal bandwidth usage profile (BUP) for each deployed node. Unfortunately, conventional methodologies do not take into account the use of energy-aware routing, and therefore, the deployed system may be overprovisioned and unnecessarily expensive. In this paper, we consider this resource assignment problem with the objective of minimizing the network deployment cost for a given energy source assignment. We first propose a resource-provisioning algorithm based on the use of temporal shortest-path routing and taking into account the node energy flow for the target deployment time period. We then introduce a methodology that incorporates energy-aware routing into the resource-assignment procedure. A genetic algorithm (GA) has been developed for this purpose. Our results show the large cost savings that an energy-aware resource assignment can achieve when compared with that done using the conventional methodology. To evaluate the quality of the resource assignments, we also develop a linear programming formulation that gives a lower bound on the total network resource assignment. Our results show that significant resource savings are possible using the proposed algorithms and the potential resource assignment benefits of energy-aware routing.

Traffic Scheduling for Energy Sustainable Vehicular Infrastructure

Roadside infrastructure can be used provide a wide variety of commercial services in vehicular ad hoc networks. One particular challenge is that of providing roadside radio coverage in highway locations where wired electricity is not available. In this case, roadside access points (APs) powered by renewable energy such as solar power, is a viable alternative. The cost of provisioning this type of roadside infrastructure is dependent on the average power consumption of the AP, and can be reduced by energy efficient scheduling. In this paper, we consider the problem of satisfying vehicle communication requirements while minimizing the energy needed by the roadside access point. The problem is formulated as a Mixed Integer Linear Program (MILP) which provides an upper bound for the performance of any realizable scheduling algorithm. We then propose a Nearest Fastest Set (NFS) scheduler that uses vehicle location and velocity inputs to address the problem. Results from a variety of experiments show that the proposed scheduling algorithm performs well when compared to the performance bound.

Energy Aware Provisioning in Solar Powered WLAN Mesh Networks

WLAN mesh networks are often installed to provide wireless coverage for temporary events. In these types of networks, the WLAN mesh nodes can sometimes be operated using an energy sustainable source such as solar power. Resource provisioning consists of pre-assigning each node with a solar panel and battery combination that is sufficient to prevent node outage for the duration of the deployment. This is done by assuming a temporal load profile for each node, which is then used to perform the assignment using historical solar insolation data for the desired deployment location. Unfortunately, this methodology cannot take into account the state dependencies which occur when the network uses energy aware routing, and therefore the system may be over-provisioned. In this paper we propose a methodology for WLAN mesh node resource assignment that incorporates energy aware routing into the assignment algorithm. The problem consists of determining a network-wide minimum cost resource assignment subject to satisfying the input load profile. A genetic algorithm (GA) has been developed for this purpose. Our results show the large resource savings that energy aware resource assignment can achieve when compared to that done using the conventional methodology. We also study the competitive ratio of both resource assignment schemes and show that for small traffic overloading, energy aware routing performs better than shortest path routing in networks which are provisioned using the proposed methodology.

Solar Powered WLAN Mesh Network Provisioning for Temporary Deployments

WLAN mesh networks are often installed to provide wireless coverage for temporary events. In many of these cases, the WLAN mesh nodes can be operated using an energy sustainable source such as solar power. Node resource assignment consists of provisioning each node with a solar panel and battery combination that is sufficient to prevent node outage for the duration of the deployment. In this paper we consider this resource assignment problem with the objective of minimizing the total battery cost for a given energy source assignment. A methodology and algorithms for determining this resource assignment are first given. We then study the problem in the presence of shortest path and energy aware routing. To evaluate the quality of the resource assignments, we develop a linear programming formulation which gives lower bounds on the network resource assignment. Competitive ratios for different routing algorithms are then used, which demonstrates their effectiveness. We also include the case where some of the deployed nodes are designated in advance as having a continuous power source. Our results show the resource savings which are possible using the design algorithms and the potential resource assignment benefits of energy aware routing.

Optimal Node Placement in Hybrid Solar Powered WLAN Mesh Networks

Hybrid WLAN mesh networks use a combination of nodes that are continuously powered and those that are powered using an energy sustainable source such as solar power. In this paper we consider the problem of cost-optimal placement of the energy sustainable nodes in these types of hybrid networks. We first introduce a cost model that takes into account the provisioning required to operate the solar/wind powered nodes subject to a desired node outage criterion. We then formulate the design problem as a Mixed Integer Quadratic Problem (MIQP). A branch and bound approach is used to obtain node positioning solutions and is compared with a proposed algorithm that uses optimum shortest path routes. Our results show that there is a significant improvement in cost that can be obtained using the proposed methodology and that the branch and bound approach achieves the optimum assignment for a variety of network examples.

A Modified Secure Remote Password (SRP) Protocol for Key Initialization and Exchange in Bluetooth Systems

This paper presents a novel solution to previously published weaknesses identified within the Bluetooth initialization key generation process. The current initialization key generating protocol will be replaced by a more robust technique, the Secure Remote Password protocol (SRP); the proposed algorithm is adapted to Bluetooth’s constrained environment by replacing the exponentiation operations with elliptic curve multiplications. This is followed by an analytical performance evaluation for the new protocol. The analysis suggests the suitability of the proposed BT-EC-SRP solution for the constrained environment of Bluetooth devices.

Energy Aware Basestation Placement in Solar Powered Sensor Networks

Sensor nodes are often used in outdoor locations where they can be operated using solar power. When such a network is deployed, there are usually restrictions in the way that the nodes can be positioned, and this results in a node-dependent attenuation of the usable solar energy. This effect must be taken into account when placing the basestations used to communicate with the sensor nodes. In this paper we consider the minimum-cost placement of data collecting basestation nodes so that outage-free operation of the sensor nodes is obtained. This is done by minimizing the number of basestations required when taking into account the energy costs of sensor node traffic relaying. An optimization is first formulated which gives a lower bound on the number of basestations that are required. Because of the complexity of the problem, an algorithm is proposed which can be used to do placements for practical problem sizes. The algorithm uses the result from an iterated local search as a starting point, and then uses an energy aware local optimization to obtain feasible basestation placements. Results are presented which show that the algorithm performs well for a variety of network scenarios.

Fair Flow Control in Solar Powered WLAN Mesh Networks

Wireless LAN mesh networks are used to provide Wi-Fi access for temporary events. In this type of application it is sometimes necessary to operate some of the mesh nodes using an energy sustainable source, such as solar power. When the network is deployed, each mesh node is equipped with a solar panel and battery combination which is sufficient to prevent network outage using an assumed traffic design profile. During post-deployment network operation however, the actual traffic flows may be different from that for which the nodes were originally provisioned. To prevent node outage, the network must flow control the inputs, and this should be done in as fair a manner as possible. In this paper we propose a mechanism for achieving fair flow control on a per-flow basis. We first formulate a bound which achieves the best max-min fair flow control subject to eliminating network outage. This bound is non-causal in that it uses knowledge of future solar insolation and traffic flows to determine the optimum flow control. The bound motivates a proposed causal flow control algorithm whose operation uses prediction based on access to on-line historical weather data. Our results show that the proposed algorithm eliminates node outage and performs very well compared to the optimum flow control bound for a variety of network scenarios.

Secondary Wireless Mesh Network Design Using Leased Frequency Spectra

This paper considers the design of secondary wireless mesh networks which use leased frequency channels. In a given geographic region, the available channels are individually priced and leased exclusively through a primary spectrum owner. The usage of each channel is also subject to published interference constraints so that the primary user is not adversely affected. When the network is designed and deployed, the secondary user would like to minimize the costs of using the required resources while satisfying its own traffic and interference requirements. This problem is formulated as a mixed integer optimization which gives the optimum deployment cost as a function of the secondary node positioning, routing, and frequency allocations. Because of the problems complexity, the optimum result can only be found for small problem sizes. To accommodate more practical deployments, two algorithms are proposed and their performance is compared to solutions obtained from the optimization. The first algorithm is a greedy flow-based scheme (GFB) which iterates over the individual node flows based on solving a much simpler optimization at each step. The second algorithm (ILS) uses an iterated local search whose initial solution is based on constrained shortest path routing. Our results show that the proposed algorithms perform well for a variety of network scenarios.