The increasing penetration of intermittent, unpredictable renewable energy sources such as wind energy, poses significant challenges for utility companies trying to incorporate renewable energy in their portfolio. In this work, we study the problem of conventional energy procurement in the presence of intermittent renewable resources. We model the problem as a variant of the newsvendor problem, in which the presence of renewable resources induces supply side uncertainty, and in which conventional energy may be procured in three stages to balance supply and demand. We compute closed-form expressions for the optimal energy procurement strategy and study the impact of increasing renewable penetration, and of proposed changes to the structure of electricity markets. We explicitly characterize the impact of a growing renewable penetration on the procurement policy by considering a scaling regime that models the aggregation of unpredictable renewable sources. A key insight from our results is that there is a separation between the impact of the stochastic nature of this aggregation, and the impact of market structure and forecast accuracy. Additionally, we study the impact on procurement of two proposed changes to the market structure: the addition and the placement of an intermediate market. We show that addition of an intermediate market does not necessarily increase the efficiency of utilization of renewable sources. Further, we show that the optimal placement of the intermediate market is insensitive to the level of renewable penetration.

Simultaneous support of multiple delay-critical application sessions such as multiuser video streaming require a paradigm shift in the design of ad-hoc wireless networks. Instead of the conventional layered approach, cross-layer optimization is needed for more efficient resource allocation, across the protocol stack and among multiple users. In this work, we extend our previous effort in joint capacity and flow assignment at the MAC and network layers, to include rate allocation at the application layer of each user. The proposed optimization aims to minimize the tradeoff between encoded video quality of all users versus overall network congestion. Compared to a scheme with oblivious layers, where capacity, flow and video rates are assigned individually, simulation results show significant performance gain of our proposed cross-layer approach, in terms of maximum sustainable rate and quality of the video streams.

This paper investigates detection mechanisms for time hopping pulse position modulated multiple access systems in both additive white Gaussian noise environment and fading environment. In such systems, the raw data is not linearly related to the received signal. One technique is to express the pulse position modulated signal as the sum of linearly modulated signals with the input being a nonlinear function of the raw data. This reduces the system to an equivalent pulse amplitude modulated system with significant increase in complexity. We present two new lower complexity detectors. The first detector uses the properties of the pulse correlation matrix to develop a lower complexity detector. The second detector relies on the knowledge of the time-hopping sequence to despread the received signal. The detection is then done on chip-by-chip basis. The performance of these detectors is compared in terms of the probability of at least one user being in error and the average number of correctly decoded users.

Orthogonal Frequency Division Multiple Access (OFDMA) is an emerging multiple access technology. In this paper, we consider OFDMA in the context of fixed wireless networks. This paper addresses the problem of assigning subcarriers and bits to point-to-point wireless links in the presence of cochannel interference and Rayleigh fading. The objective is to minimize the total transmitted power over the entire network while satisfying the data rate requirement of each link. We formulate this problem as a constrained optimization problem and present centralized algorithms. The simulation results show that our approach results in an efficient assignment of subcarriers and transmitter power levels in terms of the energy required for transmitting each bit of information. However, centralized algorithms require knowledge of the entire network topology and channel characteristics of every link. In a practical scenario, that would not be the situation and there is a need for distributed rate allocation algorithms. To address this need, we also present a distributed algorithm for allocating subcarriers and bits in order to satisfy the rate requirements of the links.

With the growing interest in wireless sensor networks, techniques for their systematic analysis design and optimization are essential. Despite numerous research efforts in optimizing hardware, algorithms and protocols for these networks, it remains largely unexplored how these innovations can be all tied together to design a sensor network for a specific practical application. We propose a methodology that starts from four independent quality of service (QoS) parameters and allows the user to completely and unambiguously describe the desired performance, without having to deal with the details of individual devices or protocols. By making appropriate choices in terms of device capabilities and run-time techniques, a design can be positioned in this four-dimensional QoS space. Furthermore, we describe a technique to explore the associated tradeoffs at design time, using both analytical expressions and simulations. To illustrate the benefits of our approach, a design example is worked out, which shows a five fold improvement in network operational lifetime by adapting the event reporting delay.

Sensor networks are deployed to monitor the physical world and to provide relevant data to the users. An important question in such networks is to estimate the number of sensors required to achieve complete coverage of the desired region. The number of sensors required would depend upon the physical characteristics of the individual sensors as well as the nature of the target. In this paper, we address the problem of finding the critical density of sensors for complete coverage. We use an exposure-based model to find the number of sensors required to cover an area for given sensor and target characteristics. The accuracy of the results is established via simulations.

We demonstrate that the dynamic behavior of queue and average window is determined predominantly by the stability of TCP/RED, not by AIMD probing nor noise traffic. We develop a general multi-link multi-source model for TCP/RED and derive a local stability condition in the case of a single link with heterogeneous sources. We validate our model with simulations and illustrate the stability region of TCP/RED. These results suggest that TCP/RED becomes unstable when delay increases, or more strikingly, when link capacity increases. The analysis illustrates the difficulty of setting RED parameters to stabilize TCP: they can be tuned to improve stability, but only at the cost of large queues even when they are dynamically adjusted. Finally, we present a simple distributed congestion control algorithm that maintains stability for arbitrary network delay, capacity, load and topology.