ORCID Profile
0000-0003-0362-2844
Current Organisations
Commonwealth Scientific and Industrial Research Organisation
,
Australian National University
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Analysis of Algorithms and Complexity | Distributed Computing | Networking and Communications
Expanding Knowledge in the Information and Computing Sciences | Mobile Data Networks and Services |
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2011
Publisher: CRC Press
Date: 05-08-2014
DOI: 10.1201/B17231
Publisher: ACM
Date: 21-05-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2021
Publisher: ACM
Date: 07-11-2018
Publisher: Informa UK Limited
Date: 2005
Publisher: ACM
Date: 16-06-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Publisher: ACM
Date: 12-06-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Publisher: ACM
Date: 16-06-2023
Publisher: ACM
Date: 17-11-2021
Publisher: IEEE
Date: 04-2009
Publisher: Association for Computing Machinery (ACM)
Date: 11-08-2006
Abstract: Traditional studies of routing problems often assumed strict preferences on paths, by eliminating ambiguity in path comparisons, or imposing a priori deterministic tie-breaking. Such an assumption is outpaced by today's common practice of non-deterministic,multi-path routing, which is crucial to traffic engineering, QoS routing, multicasting and virtual private networking. A pair of paths may be incomparable or equally preferred. In the presence of ambiguous preferences at pairs, or even multiple collections of paths, a challenge is to ensure robustness in the complex and sophisticated situations of policy-based routing where heterogeneous routing policies are allowed among routing systems. This paper presents an extensive study of policy-based routing with non-strict preferences, deriving sufficient conditions that ensure the existence, optimality and asynchronous convergence of stable routings.
Publisher: Association for Computing Machinery (ACM)
Date: 28-10-2014
DOI: 10.1145/2663492
Abstract: Nowadays digital services, such as cloud computing and network access services, allow dynamic resource allocation and virtual resource isolation. This trend can create a new paradigm of flexible pricing schemes. A simple pricing scheme is to allocate multiple isolated service classes with differentiated prices, namely Paris Metro Pricing (PMP). The benefits of PMP are its simplicity and applicability to a wide variety of general digital services, without considering specific performance guarantees for different service classes. The central issue of our study is whether PMP is economically viable, namely whether it will produce more profit for the service provider and whether it will achieve more social welfare. Prior studies had only considered specific models and arrived at conflicting conclusions. In this article, we identify unifying principles in a general setting and derive general sufficient conditions that can guarantee the viability of PMP. We further apply the results to analyze various ex les of digital services.
Publisher: ACM
Date: 16-05-2017
Publisher: Association for Computing Machinery (ACM)
Date: 10-10-2016
DOI: 10.1145/2955089
Abstract: Traditional studies of combinatorial auctions often only consider linear constraints. The rise of smart grid presents a new class of auctions, characterized by quadratic constraints. This article studies the complex-demand knapsack problem , in which the demands are complex valued and the capacity of supplies is described by the magnitude of total complex-valued demand. This naturally captures the power constraints in alternating current electric systems. In this article, we provide a more complete study and generalize the problem to the multi-minded version, beyond the previously known ½-approximation algorithm for only a subclass of the problem. More precisely, we give a truthful polynomial-time approximation scheme (PTAS) for the case φ ϵ [0,π / 2 - δ] and a truthful fully polynomial-time approximation scheme (FPTAS), which fully optimizes the objective function but violates the capacity constraint by at most (1 + ϵ), for the case φ ϵ (π / 2, π - δ], where φ is the maximum argument of any complex-valued demand and φ, δ 0 are arbitrarily small constants. We complement these results by showing that, unless P=NP, neither a PTAS for the case φ ϵ (φ / 2, φ - δ] nor any bi-criteria approximation algorithm with polynomial guarantees for the case when φ is arbitrarily close to π (that is, when δ is arbitrarily close to 0) can exist.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2018
Publisher: IEEE
Date: 2013
Publisher: ACM
Date: 12-06-2018
Publisher: ACM
Date: 21-06-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2016
Publisher: arXiv
Date: 2022
Publisher: IEEE
Date: 10-2018
Publisher: Association for Computing Machinery (ACM)
Date: 06-09-2022
DOI: 10.1145/3549550
Abstract: Data sensing and gathering is an essential task for various information-driven services in smart cities. On the one hand, Internet of Things (IoT) sensors can be deployed at certain fixed locations to capture data reliably but suffer from limited sensing coverage. On the other hand, data can also be gathered dynamically through crowdsensing contributed by voluntary users but suffer from its unreliability and the lack of incentives for users’ contributions. In this article, we explore an integrated paradigm called “ hybrid sensing ” that harnesses both IoT-sensing and crowdsensing in a complementary manner. In hybrid sensing, users are incentivized to provide sensing data not covered by IoT sensors and provide crowdsourced feedback to assist in calibrating IoT-sensing. Their contributions will be rewarded with credits that can be redeemed to retrieve synthesized information from the hybrid system. In this article, we develop a hybrid sensing system that supports explicit user privacy—IoT sensors are obscured physically to prevent capturing private user data, and users interact with a crowdsensing server via a privacy-preserving protocol to preserve their anonymity. A key application of our system is smart parking, by which users can inquire and find the available parking spaces in outdoor parking lots. We implemented our hybrid sensing system for smart parking and conducted extensive empirical evaluations. Finally, our hybrid sensing system can be potentially applied to other information-driven services in smart cities.
Publisher: ACM
Date: 21-06-2016
Publisher: IEEE
Date: 03-2012
Publisher: ACM
Date: 21-06-2016
Publisher: Elsevier BV
Date: 11-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2017
Publisher: ACM
Date: 12-06-2020
Publisher: ACM
Date: 12-06-2020
Publisher: IEEE
Date: 04-2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2020
Publisher: Springer Science and Business Media LLC
Date: 07-11-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2011
Publisher: IGI Global
Date: 2010
DOI: 10.4018/978-1-61520-855-5.CH001
Abstract: Because of the increasing number of erse routing protocols proposed to deal with the network dynamics in mobile ad hoc networks (MANETs), the heterogeneity of MANETs has increased dramatically. While many of these extant proposals only concern enhancing routing in a single domain, little attention has been given to the interoperations among heterogeneous MANETs. Moreover, the existing inter-domain routing protocols (i.e., BGP) that have been designed for the Internet cannot cope with the new challenges derived from the MANETs, such as (1) the rapid dynamic changes of network topology due to mobility, and (2) the larger ersity in intra-domain ad hoc routing protocols. In this chapter, the authors address some of the major challenges and identify new directions to the development of seamless inter-domain routing for enabling end-to-end communications over heterogeneous MANET domains.
Publisher: ACM
Date: 22-09-2009
Publisher: IEEE
Date: 03-2010
Publisher: IEEE
Date: 04-2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: ACM
Date: 16-05-2017
Publisher: IEEE
Date: 03-2010
Publisher: IEEE
Date: 11-2010
Publisher: IEEE
Date: 06-2011
Publisher: Springer International Publishing
Date: 2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2018
Publisher: IEEE
Date: 06-2017
Publisher: Elsevier BV
Date: 09-2003
Publisher: IEEE
Date: 03-2010
Publisher: ACM
Date: 12-06-2018
Publisher: ACM
Date: 28-06-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2003
Publisher: IEEE
Date: 10-2015
Publisher: IEEE
Date: 05-2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2016
Publisher: Vilnius Gediminas Technical University
Date: 02-10-2015
DOI: 10.3846/16484142.2015.1079237
Abstract: We present a novel approach to developing a vehicle communication platform consisting of a low-cost, open-source hardware for moving vehicle data to a secure server, a Web Application Programming Interface (API) for the provision of third-party services, and an intuitive user dashboard for access control and service distribution. The CloudThink infrastructure promotes the commoditization of vehicle telematics data by facilitating easier, flexible, and more secure access. It enables drivers to confidently share their vehicle information across multiple applications to improve the transportation experience for all stakeholders, as well as to potentially monetize their data. The foundations for an application ecosystem have been developed which, taken together with the fair value for driving data and low barriers to entry, will drive adoption of CloudThink as the standard method for projecting physical vehicles into the cloud. The application space initially consists of a few fundamental and important applications (vehicle tethering and remote diagnostics, road-safety monitoring, and fuel economy analysis) but as CloudThink begins to gain widespread adoption, the multiplexing of applications on the same data structure and set will accelerate its adoption.
Publisher: ACM
Date: 18-11-2020
Publisher: Elsevier BV
Date: 02-2019
Publisher: arXiv
Date: 2022
Publisher: ACM
Date: 17-11-2021
Publisher: Association for Computing Machinery (ACM)
Date: 11-10-2017
Abstract: This paper studies the problem of utilizing energy storage systems to perform demand-response in microgrids. The objective is to minimize the operational cost while balancing the supply-and-demand mismatch. The design space is to select and schedule a subset of heterogeneous storage devices that arrive online with different availabilities. Designing a performance-optimized solution is challenging due to the existence of mixed packing and covering constraints in a combinatorial problem, and the essential need for online design. We devise an online algorithm and show that it achieves logarithmic bi-criteria competitive ratio. Experimental results demonstrate the effectiveness of our algorithm.
Publisher: ACM
Date: 02-09-2017
Publisher: ACM
Date: 21-06-2016
Publisher: IEEE
Date: 06-2008
Publisher: IEEE
Date: 2006
Publisher: Now Publishers
Date: 2018
DOI: 10.1561/3100000017
Publisher: IEEE
Date: 07-2012
Publisher: ACM
Date: 18-11-2020
Publisher: Springer Nature Switzerland
Date: 2022
Publisher: IEEE
Date: 07-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2018
Publisher: IEEE
Date: 08-2014
Publisher: IEEE
Date: 10-2015
Publisher: ACM
Date: 15-06-2019
Publisher: Association for Computing Machinery (ACM)
Date: 13-07-2020
DOI: 10.1145/3392051
Abstract: Timely processing has been increasingly required on smart IoT devices, which leads to directly implementing information processing tasks on an IoT device for bandwidth savings and privacy assurance. Particularly, monitoring and tracking the observed signals in continuous form are common tasks for a variety of near real-time processing IoT devices, such as in smart homes, body-area, and environmental sensing applications. However, these systems are likely low-cost resource-constrained embedded systems, equipped with compact memory space, whereby the ability to store the full information state of continuous signals is limited. Hence, in this article,* we develop solutions of efficient timely processing embedded systems for online classification and tracking of continuous signals with compact memory space. Particularly, we focus on the application of smart plugs that are capable of timely classification of appliance types and tracking of appliance behavior in a standalone manner. We implemented a smart plug prototype using low-cost Arduino platform with small amount of memory space to demonstrate the following timely processing operations: (1) learning and classifying the patterns associated with the continuous power consumption signals and (2) tracking the occurrences of signal patterns using small local memory space. Furthermore, our system designs are also sufficiently generic for timely monitoring and tracking applications in other resource-constrained IoT devices.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2008
Publisher: Association for Computing Machinery (ACM)
Date: 19-12-2019
DOI: 10.1145/3369392
Abstract: The Internet-of-Things (IoT) has engendered a new paradigm of integrated sensing and actuation systems for intelligent monitoring and control of smart homes and buildings. One viable manifestation is that of IoT-empowered smart lighting systems, which rely on the interplay between smart light bulbs (equipped with controllable LED devices and wireless connectivity) and mobile sensors (possibly embedded in users’ wearable devices such as smart watches, spectacles, and gadgets) to provide automated illuminance control functions tailored to users’ preferences (e.g., of brightness, color intensity, or color temperature). Typically, practical deployment of these systems precludes the adoption of sophisticated but costly location-aware sensors capable of accurately mapping out the details of a dynamic operational environment. Instead, cheap oblivious mobile sensors are often utilized, which are plagued with uncertainty in their relative locations to sensors and light bulbs. The imposed volatility, in turn, impedes the design of effective smart lighting systems for uncertain indoor environments with multiple sensors and light bulbs. With this in view, the present article sheds light on the adaptive control algorithms and modeling of such systems. First, a general model formulation of an oblivious multisensor illuminance control problem is proposed, yielding a robust framework agnostic to a dynamic surrounding environment and time-varying background light sources. Under this model, we devise efficient algorithms inducing continuous adaptive lighting control that minimizes energy consumption of light bulbs while meeting users’ preferences. The algorithms are then studied under extensive empirical evaluations in a proof-of-concept smart lighting testbed featuring LIFX programmable bulbs and smartphones (deployed as light sensing units). Lastly, we conclude by discussing the potential improvements in hardware development and highlighting promising directions for future work.
Publisher: ACM
Date: 28-06-2022
Publisher: ACM
Date: 15-09-2008
Publisher: ACM
Date: 18-08-2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: ACM
Date: 20-09-2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2017
Publisher: ACM
Date: 21-06-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2017
Publisher: ACM
Date: 16-05-2017
Publisher: ACM
Date: 16-05-2017
Publisher: Association for Computing Machinery (ACM)
Date: 14-06-2013
Abstract: Microgrids represent an emerging paradigm of future electric power systems that can utilize both distributed and centralized generations. Two recent trends in microgrids are the integration of local renewable energy sources (such as wind farms) and the use of co-generation ( i.e., to supply both electricity and heat). However, these trends also bring unprecedented challenges to the design of intelligent control strategies for microgrids. Traditional generation scheduling paradigms rely on perfect prediction of future electricity supply and demand. They are no longer applicable to microgrids with unpredictable renewable energy supply and with co-generation (that needs to consider both electricity and heat demand). In this paper, we study online algorithms for the microgrid generation scheduling problem with intermittent renewable energy sources and co-generation, with the goal of maximizing the cost-savings with local generation. Based on the insights from the structure of the offline optimal solution, we propose a class of competitive online algorithms, called CHASE (Competitive Heuristic Algorithm for Scheduling Energy-generation), that track the offline optimal in an online fashion. Under typical settings, we show that CHASE achieves the best competitive ratio among all deterministic online algorithms, and the ratio is no larger than a small constant 3. We also extend our algorithms to intelligently leverage on limited prediction of the future, such as near-term demand or wind forecast. By extensive empirical evaluations using real-world traces, we show that our proposed algorithms can achieve near offline-optimal performance. In a representative scenario, CHASE leads to around 20% cost reduction with no future look-ahead, and the cost reduction increases with the future look-ahead window.
Publisher: ACM
Date: 11-06-2014
Publisher: ACM
Date: 17-08-2020
Publisher: arXiv
Date: 2020
Publisher: CRC Press
Date: 18-11-2015
DOI: 10.1201/B19065
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2011
Publisher: ACM
Date: 21-06-2016
Publisher: ACM
Date: 22-08-2008
Publisher: ACM
Date: 14-07-2015
Publisher: IEEE
Date: 2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2020
Publisher: Springer Nature Switzerland
Date: 2023
Location: No location found
Location: Australia
Start Date: 2020
End Date: 12-2023
Amount: $396,000.00
Funder: Australian Research Council
View Funded Activity