Packet scheduling for priority based transmission in energy harvesting sensors

In this paper, we determine packet scheduling policies for efficient power management in Energy Harvesting Sensors (EHS) which have to transmit packets of high and low priorities over a fading channel. We assume that incoming packets are stored in a buffer and the quality of service for a particular type of message is determined by the expected waiting time of packets of that type of message. The sensors are constrained to work with the energy that they garner from the environment. We derive transmit policies which minimize the sum of expected waiting times of the two types of messages, weighted by penalties. First, we show that for schemes with a constant rate of transmission, under a decoupling approximation, a form of truncated channel inversion is optimal. Using this result, we derive optimal solutions that minimize the weighted sum of the waiting times in the different queues.

Loss ratio of the EDF scheduling policy with early discarding technique

This paper considers a firm real-time M/M/1 system, where jobs have stochastic deadlines till the end of service. A method for approximately specifying the loss ratio of the earliest-deadline-first scheduling policy along with exit control through the early discarding technique is presented. This approximation uses the arrival rate and the mean relative deadline, normalized with respect to the mean service time, for exponential and uniform distributions of relative deadlines. Simulations show that the maximum approximation error is less than 4% and 2% for the two distributions, respectively, for a wide range of arrival rates and mean relative deadlines. (C) 2013 Elsevier B.V. All rights reserved.

Joint evaluation of channel feedback schemes, rate adaptation, and scheduling in OFDMA downlinks with feedback delays

Orthogonal frequency-division multiple access (OFDMA) systems divide the available bandwidth into orthogonal subchannels and exploit multiuser diversity and frequency selectivity to achieve high spectral efficiencies. However, they require a significant amount of channel state feedback for scheduling and rate adaptation and are sensitive to feedback delays. We develop a comprehensive analysis for OFDMA system throughput in the presence of feedback delays as a function of the feedback scheme, frequency-domain scheduler, and rate adaptation rule. Also derived are expressions for the outage probability, which captures the inability of a subchannel to successfully carry data due to the feedback scheme or feedback delays. Our model encompasses the popular best-n and threshold-based feedback schemes and the greedy, proportional fair, and round-robin schedulers that cover a wide range of throughput versus fairness tradeoff. It helps quantify the different robustness of the schedulers to feedback overhead and delays. Even at low vehicular speeds, it shows that small feedback delays markedly degrade the throughput and increase the outage probability. Further, given the feedback delay, the throughput degradation depends primarily on the feedback overhead and not on the feedback scheme itself. We also show how to optimize the rate adaptation thresholds as a function of feedback delay.

Experiences with a centralized scheduling approach for performance management of IEEE 802.11 wireless LANs

We present a centralized integrated approach for: 1) enhancing the performance of an IEEE 802.11 infrastructure wireless local area network (WLAN), and 2) managing the access link that connects the WLAN to the Internet. Our approach, which is implemented on a standard Linux platform, and which we call ADvanced Wi-fi Internet Service EnhanceR (ADWISER), is an extension of our previous system WLAN Manager (WM). ADWISER addresses several infrastructure WLAN performance anomalies such as mixed-rate inefficiency, unfair medium sharing between simultaneous TCP uploads and downloads, and inefficient utilization of the Internet access bandwidth when Internet transfers compete with LAN-WLAN transfers, etc. The approach is via centralized queueing and scheduling, using a novel, configurable, cascaded packet queueing and scheduling architecture, with an adaptive service rate. In this paper, we describe the design of ADWISER and report results of extensive experimentation conducted on a hybrid testbed consisting of real end-systems and an emulated WLAN on Qualnet. We also present results from a physical testbed consisting of one access point (AP) and a few end-systems.

Power-optimal scheduling for a green base station with delay constraints

We consider a power optimization problem with average delay constraint on the downlink of a Green Base-station. A Green Base-station is powered by both renewable energy such as solar or wind energy as well as conventional sources like diesel generators or the power grid. We try to minimize the energy drawn from conventional energy sources and utilize the harvested energy to the maximum extent. Each user also has an average delay constraint for its data. The optimal action consists of scheduling the users and allocating the optimal transmission rate for the chosen user. In this paper, we formulate the problem as a Markov Decision Problem and show the existence of a stationary average-cost optimal policy. We also derive some structural results for the optimal policy.

Joint Antenna Selection and Frequency-Domain Scheduling in OFDMA Systems with Imperfect Estimates from Dual Pilot Training Scheme

Transmit antenna selection (AS) has been adopted in contemporary wideband wireless standards such as Long Term Evolution (LTE). We analyze a comprehensive new model for AS that captures several key features about its operation in wideband orthogonal frequency division multiple access (OFDMA) systems. These include the use of channel-aware frequency-domain scheduling (FDS) in conjunction with AS, the hardware constraint that a user must transmit using the same antenna over all its assigned subcarriers, and the scheduling constraint that the subcarriers assigned to a user must be contiguous. The model also captures the novel dual pilot training scheme that is used in LTE, in which a coarse system bandwidth-wide sounding reference signal is used to acquire relatively noisy channel state information (CSI) for AS and FDS, and a dense narrow-band demodulation reference signal is used to acquire accurate CSI for data demodulation. We analyze the symbol error probability when AS is done in conjunction with the channel-unaware, but fair, round-robin scheduling and with channel-aware greedy FDS. Our results quantify how effective joint AS-FDS is in dispersive environments, the interactions between the above features, and the ability of the user to lower SRS power with minimal performance degradation.

Joint Evaluation of Reduced Feedback Scheme, Scheduling, and Rate Adaptation in OFDMA Systems with Feedback Delays

Orthogonal frequency division multiple access (OFDMA) systems exploit multiuser diversity and frequency-selectivity to achieve high spectral efficiencies. However, they require considerable feedback for scheduling and rate adaptation, and are sensitive to feedback delays. We develop a comprehensive analysis of the OFDMA system throughput as a function of the feedback scheme, frequency-domain scheduler, and discrete rate adaptation rule in the presence of feedback delays. We analyze the popular best-n and threshold-based feedback schemes. We show that for both the greedy and round-robin schedulers, the throughput degradation, given a feedback delay, depends primarily on the fraction of feedback reduced by the feedback scheme and not the feedback scheme itself. Even small feedback delays at low vehicular speeds are shown to significantly degrade the throughput. We also show that optimizing the link adaptation thresholds as a function of the feedback delay can effectively counteract the detrimental effect of delays.

Joint Routing, Scheduling and Power Control in Multihop MIMO Networks with MAC and Broadcast Links

We consider the problem of joint routing, scheduling and power control in a multihop wireless network when the nodes have multiple antennas. We focus on exploiting the multiple degrees-of-freedom available at each transmitter and receiver due to multiple antennas. Specifically we use multiple antennas at each node to form multiple access and broadcast links in the network rather than just point to point links. We show that such a generic transmission model improves the system performance significantly. Since the complexity of the resulting optimization problem is very high, we also develop efficient suboptimal solutions for joint routing, scheduling and power control in this setup.

Scheduling for Fading Channels Under Partial Channel Information

We consider a scheduler for the downlink of a wireless channel when only partial channel-state information is available at the scheduler. We characterize the network stability region and provide two throughput-optimal scheduling policies. We also derive a deterministic bound on the mean packet delay in the network. Finally, we provide a throughput-optimal policy for the network under QoS constraints when real-time and rate-guaranteed data traffic may be present.

Joint Scheduling & Jamming for Data Secrecy in Wireless Networks

The broadcast nature of the wireless medium jeopardizes secure transmissions. Cryptographic measures fail to ensure security when eavesdroppers have superior computational capability; however, it can be assured from information theoretic security approaches. We use physical layer security to guarantee non-zero secrecy rate in single source, single destination multi-hop networks with eavesdroppers for two cases: when eavesdropper locations and channel gains are known and when their positions are unknown. We propose a two-phase solution which consists of finding activation sets and then obtaining transmit powers subject to SINR constraints for the case when eavesdropper locations are known. We introduce methods to find activation sets and compare their performance. Necessary but reasonable approximations are made in power minimization formulations for tractability reasons. For scenarios with no eavesdropper location information, we suggest vulnerability region (the area having zero secrecy rate) minimization over the network. Our results show that in the absence of location information average number of eavesdroppers who have access to data is reduced.

A distributed TDMA slot scheduling algorithm for spatially correlated contention in WSNs

In wireless sensor networks (WSNs) the communication traffic is often time and space correlated, where multiple nodes in a proximity start transmitting at the same time. Such a situation is known as spatially correlated contention. The random access methods to resolve such contention suffers from high collision rate, whereas the traditional distributed TDMA scheduling techniques primarily try to improve the network capacity by reducing the schedule length. Usually, the situation of spatially correlated contention persists only for a short duration and therefore generating an optimal or sub-optimal schedule is not very useful. On the other hand, if the algorithm takes very large time to schedule, it will not only introduce additional delay in the data transfer but also consume more energy. To efficiently handle the spatially correlated contention in WSNs, we present a distributed TDMA slot scheduling algorithm, called DTSS algorithm. The DTSS algorithm is designed with the primary objective of reducing the time required to perform scheduling, while restricting the schedule length to maximum degree of interference graph. The algorithm uses randomized TDMA channel access as the mechanism to transmit protocol messages, which bounds the message delay and therefore reduces the time required to get a feasible schedule. The DTSS algorithm supports unicast, multicast and broadcast scheduling, simultaneously without any modification in the protocol. The protocol has been simulated using Castalia simulator to evaluate the run time performance. Simulation results show that our protocol is able to considerably reduce the time required to schedule.

Delay optimal scheduling of a discrete-time batch service queue for point-to-point channel code rate selection

We consider the problem of characterizing the minimum average delay, or equivalently the minimum average queue length, of message symbols randomly arriving to the transmitter queue of a point-to-point link which dynamically selects a (n, k) block code from a given collection. The system is modeled by a discrete time queue with an IID batch arrival process and batch service. We obtain a lower bound on the minimum average queue length, which is the optimal value for a linear program, using only the mean (λ) and variance (σ2) of the batch arrivals. For a finite collection of (n, k) codes the minimum achievable average queue length is shown to be Θ(1/ε) as ε ↓ 0 where ε is the difference between the maximum code rate and λ. We obtain a sufficient condition for code rate selection policies to achieve this optimal growth rate. A simple family of policies that use only one block code each as well as two other heuristic policies are shown to be weakly optimal in the sense of achieving the 1/ε growth rate. An appropriate selection from the family of policies that use only one block code each is also shown to achieve the optimal coefficient σ2/2 of the 1/ε growth rate. We compare the performance of the heuristic policies with the minimum achievable average queue length and the lower bound numerically. For a countable collection of (n, k) codes, the optimal average queue length is shown to be Ω(1/ε). We illustrate the selectivity among policies of the growth rate optimality criterion for both finite and countable collections of (n, k) block codes.

Scheduling for Stable and Reliable Communication Over Multiaccess Channels and Degraded Broadcast Channels

We model communication of bursty sources: 1) over multiaccess channels, with either independent decoding or joint decoding and 2) over degraded broadcast channels, by a discrete-time multiclass processor sharing queue. We utilize error exponents to give a characterization of the processor sharing queue. We analyze the processor sharing queue model for the stable region of message arrival rates, and show the existence of scheduling policies for which the stability region converges to the information-theoretic capacity region in an appropriate limiting sense.

Fair Scheduling in Cellular Systems in the Presence of Noncooperative Mobiles

We consider the problem of ``fair'' scheduling the resources to one of the many mobile stations by a centrally controlled base station (BS). The BS is the only entity taking decisions in this framework based on truthful information from the mobiles on their radio channel. We study the well-known family of parametric alpha-fair scheduling problems from a game-theoretic perspective in which some of the mobiles may be noncooperative. We first show that if the BS is unaware of the noncooperative behavior from the mobiles, the noncooperative mobiles become successful in snatching the resources from the other cooperative mobiles, resulting in unfair allocations. If the BS is aware of the noncooperative mobiles, a new game arises with BS as an additional player. It can then do better by neglecting the signals from the noncooperative mobiles. The BS, however, becomes successful in eliciting the truthful signals from the mobiles only when it uses additional information (signal statistics). This new policy along with the truthful signals from mobiles forms a Nash equilibrium (NE) that we call a Truth Revealing Equilibrium. Finally, we propose new iterative algorithms to implement fair scheduling policies that robustify the otherwise nonrobust (in presence of noncooperation) alpha-fair scheduling algorithms.

Two timescale convergent Q-learning for sleep-scheduling in wireless sensor networks

In this paper, we consider an intrusion detection application for Wireless Sensor Networks. We study the problem of scheduling the sleep times of the individual sensors, where the objective is to maximize the network lifetime while keeping the tracking error to a minimum. We formulate this problem as a partially-observable Markov decision process (POMDP) with continuous stateaction spaces, in a manner similar to Fuemmeler and Veeravalli (IEEE Trans Signal Process 56(5), 2091-2101, 2008). However, unlike their formulation, we consider infinite horizon discounted and average cost objectives as performance criteria. For each criterion, we propose a convergent on-policy Q-learning algorithm that operates on two timescales, while employing function approximation. Feature-based representations and function approximation is necessary to handle the curse of dimensionality associated with the underlying POMDP. Our proposed algorithm incorporates a policy gradient update using a one-simulation simultaneous perturbation stochastic approximation estimate on the faster timescale, while the Q-value parameter (arising from a linear function approximation architecture for the Q-values) is updated in an on-policy temporal difference algorithm-like fashion on the slower timescale. The feature selection scheme employed in each of our algorithms manages the energy and tracking components in a manner that assists the search for the optimal sleep-scheduling policy. For the sake of comparison, in both discounted and average settings, we also develop a function approximation analogue of the Q-learning algorithm. This algorithm, unlike the two-timescale variant, does not possess theoretical convergence guarantees. Finally, we also adapt our algorithms to include a stochastic iterative estimation scheme for the intruder's mobility model and this is useful in settings where the latter is not known. Our simulation results on a synthetic 2-dimensional network setting suggest that our algorithms result in better tracking accuracy at the cost of only a few additional sensors, in comparison to a recent prior work.