arXiv subjects

Qiao Li

Publications and source records attributed to Qiao Li.

79 records · Page 5Linked to original sources

arXiv2012

An Information-Theoretic Approach to PMU Placement in Electric Power Systems

This paper presents an information-theoretic approach to address the phasor measurement unit (PMU) placement problem in electric power systems. Different from the conventional 'topological observability' based approaches, this paper advocates a much more refined, information-theoretic criterion, namely the mutual information (MI) between the PMU measurements and the power system states. The proposed MI criterion can not only include the full system observability as a special case, but also can rigorously model the remaining uncertainties in the power system states with PMU measurements, so as to generate highly informative PMU configurations. Further, the MI criterion can facilitate robust PMU placement by explicitly modeling probabilistic PMU outages. We propose a greedy PMU placement algorithm, and show that it achieves an approximation ratio of (1-1/e) for any PMU placement budget. We further show that the performance is the best that one can achieve in practice, in the sense that it is NP-hard to achieve any approximation ratio beyond (1-1/e). Such performance guarantee makes the greedy algorithm very attractive in the practical scenario of multi-stage installations for utilities with limited budgets. Finally, simulation results demonstrate near-optimal performance of the proposed PMU placement algorithm.

math.OC↗

arXiv2011

Maximal Scheduling in Wireless Networks with Priorities

We consider a general class of low complexity distributed scheduling algorithms in wireless networks, maximal scheduling with priorities, where a maximal set of transmitting links in each time slot are selected according to certain pre-specified static priorities. The proposed scheduling scheme is simple, which is easily amendable for distributed implementation in practice, such as using inter-frame space (IFS) parameters under the ubiquitous 802.11 protocols. To obtain throughput guarantees, we first analyze the case of maximal scheduling with a fixed priority vector, and formulate a lower bound on its stability region and scheduling efficiency. We further propose a low complexity priority assignment algorithm, which can stabilize any arrival rate that is in the union of the lower bound regions of all priorities. The stability result is proved using fluid limits, and can be applied to very general stochastic arrival processes. Finally, the performance of the proposed prioritized maximal scheduling scheme is verified by simulation results.

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arXiv2011

On-line Decentralized Charging of Plug-In Electric Vehicles in Power Systems

The concept of plug-in electric vehicles (PEV) are gaining increasing popularity in recent years, due to the growing societal awareness of reducing greenhouse gas (GHG) emissions, and gaining independence on foreign oil or petroleum. Large-scale deployment of PEVs currently faces many challenges. One particular concern is that the PEV charging can potentially cause significant impacts on the existing power distribution system, due to the increase in peak load. As such, this work tries to mitigate the impacts of PEV charging by proposing a decentralized smart PEV charging algorithm to minimize the distribution system load variance, so that a `flat' total load profile can be obtained. The charging algorithm is myopic, in that it controls the PEV charging processes in each time slot based entirely on the current power system states, without knowledge about future system dynamics. We provide theoretical guarantees on the asymptotic optimality of the proposed charging algorithm. Thus, compared to other forecast based smart charging approaches in the literature, the charging algorithm not only achieves optimality asymptotically in an on-line, and decentralized manner, but also is robust against various uncertainties in the power system, such as random PEV driving patterns and distributed generation (DG) with highly intermittent renewable energy sources.

math.OC↗

arXiv2011

Distributed Throughput-optimal Scheduling in Ad Hoc Wireless Networks

In this paper, we propose a distributed throughput-optimal ad hoc wireless network scheduling algorithm, which is motivated by the celebrated simplex algorithm for solving linear programming (LP) problems. The scheduler stores a sparse set of basic schedules, and chooses the max-weight basic schedule for transmission in each time slot. At the same time, the scheduler tries to update the set of basic schedules by searching for a new basic schedule in a throughput increasing direction. We show that both of the above procedures can be achieved in a distributed manner. Specifically, we propose an average consensus based link contending algorithm to implement the distributed max weight scheduling. Further, we show that the basic schedule update can be implemented using CSMA mechanisms, which is similar to the one proposed by Jiang et al. Compared to the optimal distributed scheduler in Jiang's paper, where schedules change in a random walk fashion, our algorithm has a better delay performance by achieving faster schedule transitions in the steady state. The performance of the algorithm is finally confirmed by simulation results.

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arXiv2010

Greedy Maximal Scheduling in Wireless Networks

In this paper we consider greedy scheduling algorithms in wireless networks, i.e., the schedules are computed by adding links greedily based on some priority vector. Two special cases are considered: 1) Longest Queue First (LQF) scheduling, where the priorities are computed using queue lengths, and 2) Static Priority (SP) scheduling, where the priorities are pre-assigned. We first propose a closed-form lower bound stability region for LQF scheduling, and discuss the tightness result in some scenarios. We then propose an lower bound stability region for SP scheduling with multiple priority vectors, as well as a heuristic priority assignment algorithm, which is related to the well-known Expectation-Maximization (EM) algorithm. The performance gain of the proposed heuristic algorithm is finally confirmed by simulations.

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arXiv2010

Scheduling in Wireless Networks under Uncertainties: A Greedy Primal-Dual Approach

This paper proposes a dynamic primal-dual type algorithm to solve the optimal scheduling problem in wireless networks subject to uncertain parameters, which are generated by stochastic network processes such as random packet arrivals, channel fading, and node mobilities. The algorithm is a generalization of the well-known max-weight scheduling algorithm proposed by Tassiulas et al., where only queue length information is used for computing the schedules when the arrival rates are uncertain. Using the technique of fluid limits, sample path convergence of the algorithm to an arbitrarily close to optimal solution is proved, under the assumption that the Strong Law of Large Numbers (SLLN) applies to the random processes which generate the uncertain parameters. The performance of the algorithm is further verified by simulation results. The method may potentially be applied to other applications where dynamic algorithms for convex problems with uncertain parameters are needed.

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arXiv2009

Scheduling in Multi-hop Wireless Networks with Priorities

In this paper we consider prioritized maximal scheduling in multi-hop wireless networks, where the scheduler chooses a maximal independent set greedily according to a sequence specified by certain priorities. We show that if the probability distributions of the priorities are properly chosen, we can achieve the optimal (maximum) stability region using an i.i.d random priority assignment process, for any set of arrival processes that satisfy Law of Large Numbers. The pre-computation of the priorities is, in general, NP-hard, but there exists polynomial time approximation scheme (PTAS) to achieve any fraction of the optimal stability region. We next focus on the simple case of static priority and specify a greedy priority assignment algorithm, which can achieve the same fraction of the optimal stability region as the state of art result for Longest Queue First (LQF) schedulers. We also show that this algorithm can be easily adapted to satisfy delay constraints in the large deviations regime, and therefore, supports Quality of Service (QoS) for each link.

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