Gustavo Vejarano

Stability Analysis of Reservation-Based Scheduling Policies in Wireless Networks

A major challenge in wireless networks is the ability to maximize the throughput. High throughput in a wireless network requires a relatively low complex scheduling policy with a provable efficiency ratio, which is a measure of the performance of the policy in terms of throughput and stability. For most scheduling policies that achieve provable ratios, at the onset of every frame, a selection is made of a subset of links to transmit data in the immediately following frame. In this paper, we propose a policy that allows links to transmit data in any future frame by means of frame reservations. The new, reservation-based distributed scheduling approach will improve the capacity of the system and provide greater throughput. First, we create a framework to analyze the stability of reservation-based scheduling systems. Then, to demonstrate its efficacy, we propose a reservation-based distributed scheduling policy for IEEE 802.16 mesh networks and use the new framework to find sufficient conditions for the stability of the network under this policy, i.e., we find a lower bound for its efficiency ratio. Finally, by means of simulation, we validate the mathematical analysis and compare the performance of our policy with nonreservation-based policies.

WiMAX-RBDS-Sim: an OPNET simulation framework for IEEE 802.16 mesh networks

In this paper, a simulation model for IEEE 802.16 (WiMAX) wireless mesh networks with distributed scheduling is developed. It provides a framework for the evaluation of reservation-based distributed scheduling (RBDS) policies at the medium access control (MAC) layer. The simulation model, called WiMAX-RBDS-Sim, is developed under the OPNET event-driven simulation environment. It provides interfaces for the integration of RBDS policies and link-establishment algorithms. As an example of the use of WiMAX-RBDS-Sim, a new RBDS policy called Sliced-GM-RBDS is proposed and evaluated. This policy is based on the GM-RBDS policy proposed in [27]. The WiMAX-RBDS-Sim simulation results show that Sliced-GM-RBDS outperforms GM-RBDS in terms of network stability. A link-establishment algorithm is also evaluated with WiMAX-RBDS-Sim to determine the time required for the completion of link establishments across the network. Finally, the performance of WiMAX-RBDS-Sim is evaluated in terms of simulation speed and memory usage.

Stability region adaptation using transmission power control for transport capacity optimization in IEEE 802.16 wireless mesh networks

Transmission power control in multihop wireless networks is a challenging problem due to the effects that different node transmission powers have across the layers of the protocol stack. In this paper, we study the problem of transmission power control in IEEE 802.16 mesh networks with distributed scheduling. We consider the effects of transmission power control on the link-scheduling performance when a set of end-to-end flows established in the network are given. The problem is approached by means of the stability region of the link-scheduling policy. Specifically, the stability region is adapted using transmission-power control to the paths of the flows. This adaptation enables the flows to support higher levels of data traffic under lower levels of end-to-end delay. To the best of our knowledge, the approach of stability-region-based transmission power control has not been studied before. We propose a heuristic transmission-power-control algorithm for solving the problem of adapting the stability region to the flows. It is shown, by means of simulation, that the algorithm outperforms the transmission power control based on spatial reuse, which is a widely used approach. Also, it is shown that the solution of the algorithm has performance close to the optimal solution for moderate-sized networks, i.e., networks with no more than 25 nodes and 25 flows.

Queue-Stability-Based Transmission Power Control in Wireless Multihop Networks

In this paper, we study the problem of transmission power control and its effects on the link-scheduling performance when a set of end-to-end flows established in the network are given. This problem is approached by means of the stability region of the link-scheduling policy. The stability region is defined for link-scheduling policies as the set of input-packet rates under which the queues in the network are stable (i.e., positive recurrent). Specifically, the link-schedulings stability region is adapted to the paths of the flows such that the flows are able to support higher levels of data traffic under lower levels of end-to-end delay. To the best of our knowledge, the approach of transmission power control based on queue stability has not been studied before. Based on this approach, we propose a transmission-power-control algorithm. It is shown, by means of simulation, that the algorithm outperforms the transmission power control based on spatial reuse.

Development of a wireless sensor network for the measurement of human joint angles

The development of a wireless sensor network (WSN) that measures joint angles of the human body is reported. Its principle of operation is based on measuring the alignment of the different segments of the limb being tracked with the earths gravity and magnetic fields. The focus is on measurements at the shoulder and elbow joints. These are tracked with 3 and 2 degrees of freedom respectively. In order to validate the accuracy of the proposed WSN, experiments are performed with arm movements on each degree of freedom and the WSNs measurements are compared with those of a professional motion capture (mocap) system that uses infra-red (IR) cameras and markers. The average root mean square error (RMSE) across all degrees of freedom was found to be 1.39° and 2.18° when tested on a spherical coordinate system and human arm respectively. Finally, the causes for this increase on the RMSE are discussed in terms of the effects of the arms skin and muscles on the alignment of the sensors. It is found that when the user performs the greatest efforts to make the movements, the WSN deviates the most from the IR mocap system. In the degree of freedom that is most affected, the RMSE increases from 0.96° to 2.62°. This is an increase of 173%.

Human-motion based transmission power control in wireless body area networks

The development of a transmission power control (TPC) protocol for wireless body area networks (WBANs) is proposed. The WBAN consists of wireless sensors attached to the user. Each sensor has a transceiver and an inertial measurement unit (IMU) to measure users motion. The TPC protocol increases the WBANs lifetime by reducing the power consumption of the transceiver. The protocol is based on a mathematical model of the human motion performed by the user. It uses the model to determine the minimum transmission power required to achieve a packet delivery ratio (PDR). The TPC protocol uses the received signal strength indicator (RSSI) to characterize the channel. It uses IMU measurements to determine the parameters of the model and then decide on transmission-power levels. Also, the TPC protocol includes a method to reduce the complexity of the human-motion model to reduce the calculations the wireless sensor has to perform. The TPC protocol is implemented and tested real-time on a Shimmer2r wireless sensor. Experimental results on a bicep-curl movement show that the average power per packet decreased from 31.3mW to 19.0mW, which is a reduction of 39%, while maintaining the PDR within a 4% difference from the target PDR.

Prediction of received signal strength from human joint angles in body area networks

Focusing on movements of a human participant performing physical-therapy exercises, this paper presents an algorithm that predicts the received signal strength indicator (RSSI) of wireless sensor nodes attached to the user. The body area network (BAN) formed by the nodes is a motion capture system that measures joint angles of the user at the shoulder and elbow. In order to predict the RSSI, we first show that the wireless signal experiences severe attenuation from human-body shadowing even though distances between transmitters and receiver are less than 3 meters. Second, we show that the RSSI fluctuates periodically with regular body movements (i.e., physical-therapy exercises). We then model the movements using k-means clustering and Markov chains and determine the probability distribution of the RSSI at each state in the movement. Finally, the RSSI is predicted with a maximum a posteriori probability (MAP) detector. Experimental results show that the RSSI can be predicted with a root mean square error (RMSE) of 3.7 dB, which is an error within 4.2% of the average RSSI level, and when a prediction is made, it is valid for the next 1083 milliseconds (ms) on average.