Mahima Agumbe Suresh

On Event Detection and Localization in Acyclic Flow Networks

Acyclic flow networks, present in many infrastructures of national importance (e.g., oil and gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against these infrastructures have been proven costly and imprecise, particularly when dealing with large-scale distribution systems. In this article, to the best of our knowledge, for the first time, we investigate how mobile sensor networks can be used for optimal event detection and localization in acyclic flow networks. We propose the idea of using sensors that move along the edges of the network and detect events (i.e., attacks). To localize the events, sensors detect proximity to beacons, which are devices with known placement in the network. We formulate the problem of minimizing the cost of monitoring infrastructure (i.e., minimizing the number of sensors and beacons deployed) in a predetermined zone of interest, while ensuring a degree of coverage by sensors and a required accuracy in locating events using beacons. We propose algorithms for solving the aforementioned problem and demonstrate their effectiveness with results obtained from a realistic flow network simulator.

Towards optimal event detection and localization in acyclic flow networks

Acyclic flow networks, present in many infrastructures of national importance (e.g., oil & gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against these infrastructures, have been proven costly and imprecise, especially when dealing with large scale distribution systems. In this paper, to the best of our knowledge for the first time, we investigate how mobile sensor networks can be used for optimal event detection and localization in acyclic flow networks. Sensor nodes move along the edges of the network and detect events (i.e., attacks) and proximity to beacon nodes with known placement in the network. We formulate the problem of minimizing the cost of monitoring infrastructure (i.e., minimizing the number of sensor and beacon nodes deployed), while ensuring a degree of sensing coverage in a zone of interest and a required accuracy in locating events. We propose algorithms for solving these problems and demonstrate their effectiveness with results obtained from a high fidelity simulator.

Mobile sensor networks for optimal leak and backflow detection and localization in municipal water networks

Leak and backflow detections are essential aspects of Water Distribution Systems (WDSs) monitoring and are commonly fulfilled using approaches that are based on static sensor networks and point measurements. Alternatively, we propose a mobile, wireless sensor network solution composed of mobile sensor nodes that travel freely inside the pipes with the water flow, collect and transmit measurements in near-realtime (called sensors) and static access points (called beacons). This study complements the tremendous progress in mobile sensor technology. We formulate the sensor and beacon optimal placement task as a Mixed Integer Nonlinear Programming (MINLP) problem to maximize localization accuracy with budget constraint. Given the high time complexity of MINLP formulation, we propose a disjoint scheme that follows the strategy of splitting the sensor and beacon placement problems and determining the respective number of sensors and beacons by exhaustive search in linear time. We present a mathematical model for the joint optimization of sensor and beacon placement to minimize localization error.We propose a computationally less expensive disjoint formulation for sensor and beacon placement.We demonstrate the advantage of our solution on a sample WDS from EPANET and a virtual model city called Micropolis.

Toward Optimal Monitoring of Flow-Based Systems Using Mobile Wireless Sensor Networks

Monitoring flow-based systems (FBS) (e.g., water distribution systems, oil and gas pipelines, the human cardiovascular system) is of paramount importance considering their economic and health impacts. FBS monitoring typically has been achieved by costly, complex, static sensors that are strategically placed. To reduce the cost of monitoring, we propose a mobile wireless sensor network (WSN) system comprised of mobile sensors (their movement aided by the inherent flow in the FBS) and static beacons that aid in locating sensors. This article presents the first complete architectural design, algorithms, and protocols for optimal monitoring of FBS. Our proposed solution includes sensing and communication models, MAC and group management protocols for sensor and beacon communication, and algorithms for sensor and beacon placement. We compare our proposed solution with the state of the art through extensive simulations and a proof-of-concept system implementation. We demonstrate performance improvements, such as a dramatic reduction (a factor of 91) in the number of sensors when the sensing range is marginally (2.5 times) increased.

On Modeling the Coexistence of 802.11 and 802.15.4 Networks for Performance Tuning

The explosion in the number of 802.11 and 802.15.4 deployments is exacerbating the coexistence problem, which has been reported in the literature to cause significant performance degradation in co-located networks employing the two different wireless standards. The wireless coexistence problem has, thus far, been studied primarily using hardware, due to the lack of analytical results and good wireless coexistence simulators. This paper presents the first analytical model for coexisting 802.11 and 802.15.4 networks. We derive analytically, using Markov chains, the normalized saturation throughput under coexistence. Additionally, we propose a performance tuning method that ensures QoS and a distributed Nash-equilibrium-based method that ensures fairness. We validate our model and the tuning methods using a coexistence simulator previously developed and presented by the authors. We demonstrate that our model has a low average error smaller than 10%.

On Modeling the Coexistence of WiFi and Wireless Sensor Networks

The explosion in the number of WiFi and Wireless Sensor Network (WSN) deployments is exacerbating the coexistence problem, observed and reported in the literature as a significant performance degradation in co-located networks employing the two different wireless standards. The wireless coexistence problem has, thus far, been studied primarily using real hardware, due to the lack of analytical results and lack of good wireless coexistence models in network simulators. Thus, the progress on addressing the wireless coexistence issues has been slow. This paper presents the first analytical model and the first protocol coexistence simulator for coexisting WiFi and WSNs. We derive analytically, using Markov chains, the normalized saturated throughput of coexisting WiFi and WSNs, simulate the protocol coexistence using Monte Carlo methods, and validate our results through extensive experiments on real hardware (~4 million and ~60 million WSN and WiFi packets, respectively). These tools can be used for convenient and accurate performance estimation of medium-large scale deployments.

Analyzing Process Variants to Understand Differences in Key Performance Indices

Service delivery organizations cater similar processes across several clients. Process variants may manifest due to the differences in the nature of clients, heterogeneity in the type of cases, etc. The organization’s operational Key Performance Indices (KPIs) across these variants may vary, e.g., KPIs for some variants may be better than others. There is a need to gain insights for such variance in performance and seek opportunities to learn from well performing process variants (e.g., to establish best practices and standardization of processes) and leverage these learnings/insights on non-performing ones. In this paper, we present an approach to analyze two or more process variants, presented as annotated process maps. Our approach identifies and reasons the key differences, manifested in both the control-flow (e.g., frequent paths) and performance (e.g., flow time, activity execution times, etc.) perspectives, among these variants. The fragments within process variants where the key differences manifest are targets for process redesign and re-engineering. The proposed approach has been implemented as a plug-in in the process mining framework, ProM, and applied on real-life case studies.

On modeling single-cell IEEE 802.11 Ad-Hoc network with power saving mode

Energy efficiency is a significant aspect in wireless LANs due to the pervasive usage of mobile devices. The most effective way to save energy is turning off the radio, which is the key feature of the IEEE 802.11 power saving mode (PSM) protocol. Understanding the performance such as throughput and energy consumption of 802.11 PSM networks is important because they depend highly on the parameters we choose for contention window size, duty cycling ratio, etc. For this purpose, an analytical model is greatly preferred comparing to the tedious simulation because the former is fast, scalable and can be easily used to optimize performance. This paper presents a comprehensive analytical model for 802.11 IBSS PSM. We derive analytically, using Markov chains, the throughput, total delay and energy consumption, simulate the network using ns-3 simulator, and validate our results through extensive simulations. This model can be conveniently applied to accurately estimate and optimize the performance of single-cell 802.11 PSM ad-hoc networks.

A cyber-physical system for continuous monitoring of Water Distribution Systems

Water Distribution Systems (WDSs) are prone to events such as leaks, breaks, and chemical contamination. Continuous monitoring of WDSs for prompt response to such events is of paramount importance. WDS monitoring has been typically performed using static sensors that are strategically placed. These solutions are costly and imprecise [9] [18]. Recently mobile sensors for WDS monitoring has attracted research interest to overcome the shortcomings of static sensors [21] [14] [11]. However, most existing solutions are either unrealistic, or focus on on-demand methods (i.e., deploying sensors when presence of an event is suspected). In this paper, we propose a Cyber-Physical system (CPS) - CPWDS, for continuous monitoring of a WDS. Mobile sensors reside in the CPWDS and move with the flow of water in pipes; mobile sensors communicate with static beacons placed outside the pipes, and report sensed data; the flows in the pipes are controlled to prevent sensors from getting stuck and to ensure the sensors cover the main pipes of the WDS. We evaluate the proposed algorithms/protocols for the communication, computation and control of the CPWDS and demonstrate their performance through extensive simulations.

On the coexistence of 802.11 and 802.15.4 networks with delay constraints

Coexisting 802.11 and 802.15.4 single-cell wireless networks are experiencing significant performance degradation due to the aggressive nature of 802.11 (when compared to 802.15.4) and to their different traffic characteristics [1]. Providing tight delay guarantees to certain 802.15.4 applications (e.g., health monitoring with unsaturated, periodic traffic) is becoming increasingly infeasible, in the presence of coexisting WiFi with bursty and bandwidth-hungry traffic. Optimizing the performance of these coexisting networks (e.g., WiFi throughput maximization, while satisfying 802.15.4 deadlines) has been a challenging task, primarily due to the lack of: i) analytical models that take into consideration realistic network traffic conditions; and ii) accurate simulators for coexistence. In this paper, we address the aforementioned research challenges by modeling the transmission buffers of wireless devices as M/G/1 queues, and employ queuing theory and Markov Chain models to derive, for the first time, closed form solutions for throughput and delay in 802.11/802.15.4 coexisting networks. Using our proposed models, this paper presents a novel approach for joint MAC protocol tuning, that maximizes 802.11 throughput while satisfying delay constraints of 802.15.4. We validate our proposed solutions and models through new 802.11/802.15.4 coexistence capabilities in the ns-3 simulator (important for the research community).