Kartavya Neema

Search delay and success in combined social and communication networks

This paper addresses the problem of search with local information in combined social and communication networks. Social networks are modeled with short-range and long-range connections representing small-world and scale-free network characteristics. By distinguishing the delay and success probability on different social links, the end-to-end delay distribution and success probability are derived as functions of the social separation from the destination. Also, greedy routing algorithms are developed to improve the delay and chain completion success. Then, the analysis is extended to the combined social and communication networks, where wireless communication becomes the underlay to route information with the aid of social connections. The analytical results are validated via simulated search results on a combined social and communication network. Our results show how social connections can help reduce the search delay and increase the success probability in chain completion.

Complexity enabled design space exploration

The proposed paper presents a framework for complexity enabled design space exploration. A circuit problem is introduced where different designs are generated from a component library to create a low pass filter circuit. Performance and complexity metrics are defined to measure the fitness of the design. A scheme for complexity enabled design space exploration is introduced and the results obtained are compared to the traditional performance based exploration. It is found that the complexity enabled exploration results in identification of regions within the performance-complexity trade space which are difficult to obtain using a performance based exploration. Characteristic features of designs that result in high performance but low complexity are also identified. Later a scheme for local design space exploration is proposed which investigates the designs in the nearest neighborhood of a particular design. This provides insights about the flexibility and adaptability of the design.

Search in Combined Social and Wireless Communication Networks: Delay and Success Analysis

This paper models and analyzes the problem of search (navigation) with local information in combined social and wireless communication networks. Social networks are modeled with short-range and long-range connections representing small-world and scale-free network characteristics. By distinguishing the delay and success probability on different link types, the end-to-end delay distribution and success probability are first derived as functions of the social separation from the destination. New routing algorithms are then developed to improve the delay and chain completion success, and the effects of delay deadline on success probability are evaluated. The analysis is extended to the multi-layer combined social and communication network model, where wireless communication becomes the underlay to route information with the aid of social connections. The analytical results on delay and success probability are validated by comparing them with search results on a real-world social and communication network. Results of this paper show how social connections can help reduce the search delay and increase the success probability in chain completion that runs on interdependent social and wireless communication network structures.

Consensus based Heuristic Algorithm for Distributed Sensor Management

This paper addresses the problem of sensor-target allocation for multi-target tracking where a group of sensors is dynamically allocated to targets with the goal of maximizing tracking performance. We propose the Consensus-Based Heuristic Algorithm (CBHA) that works in two phases to solve the sensor-target allocation problem. The first phase combines the benefits of heuristic and consensus algorithms to quickly converge to a feasible solution. In the second phase, the CBHA iteratively improves the allocation, eventually leading toward a global optimal. CBHA is innovative in its ability to achieve a faster convergence to a feasible solution, and thus can be useful under conditions such as (a) rapidly changing network topologies in a highly dynamic environment, (b) discovery of pop-up threats leading to algorithm re-run, and (c) loss of a resource (node or link). Furthermore, the algorithm can be stopped any time after the first phase is completed as it always results in a feasible assignment in a dynamic and contested environment. We demonstrate the effectiveness of the algorithm using representative simulation results.

Distributed Fault Detection and Isolation for Kalman Consensus Filter

This paper deals with the problem of developing a distributed fault detection methodology for recently developed distributed estimation algorithm called Kalman Consensus Filter (KCF). We extended the residual covariance matching techniques, developed for detecting faults in centralized Kalman filters, and use it for distributed fault detection in KCF. Faults present due to faulty sensor measurements are diagnosed and isolated from the system. Specifically, faults due to change in sensor noise statistics and outliers in the sensor measurements are considered. We further develop a Robust Kalman Consensus Filter algorithm and demonstrate the effectiveness of the algorithm using simulation results.

Innovative Framework for Orbital Debris Mitigation through Satellite Rejuvenation

This paper presents a conceptual framework for orbital debris mitigation through satellite rejuvenation. Instead of developing complex robotic technologies, the concept focuses on relatively simple use of inspection and rejuvenation module designs. Our approach would inspect the dysfunctional satellite, and rejuvenate it if it is found to be serviceable. Otherwise, the approach would deorbit the dysfunctional satellite. Though only described in this paper as a concept, a review of the state of the art indicates that the concept could be advantageous to mitiage orbital debris. I. Introduction PACE systems operate in a harsh and hostile environment. Following launch, there is little flexibility to modify any aspect of their operation with the exception of software updates via uplink. This inaccessibility makes them susceptible to technological obsolescence and failures. Historical analysis indicates that approximately one out of every seven satellites launched fail before reaching their end of life (EOL). Some of these failures result from malfunction of the launch vehicle, which can either cause complete destruction of the satellite or lead to the satellite being placed in the wrong orbit. Other reasons for failures stem from breakdown of one or more components during their operation or due to collision with space debris. With each satellite costing hundreds of millions of dollars and huge capital investment involved in space missions, the space industry today has become extremely averse to risks. This environment, where cost of failure is unacceptably large, has stifled innovation and has driven space systems design towards use of greater redundancy and proven technology. We propose a unique concept for rejuvenating these defunct satellites which have either reached EOL or failed during the course of its mission. We also investigate the possibility of de-orbiting the defunct satellite in case the satellite is found to be damaged beyond repair. We believe that this will have the following advantages: 1) Greater probability of return on the huge investment involved in developing and launching space missions, 2) Extended design life, 3) Reduce development costs and risks in new satellite designs. These benefits, especially 3, will allow a greater room for innovation and development of better systems. Further, a rejuvenated satellite with regain additional maneuvering capability, thus mitigating potential orbital debris generated from the collision with other orbital debris.

Dual phase consensus algorithm for distributed sensor management

We propose the dual phase consensus algorithm (DCPA) to solve distributed sensor-target allocation for multitarget tracking. DPCA combines the benefits of greedy and consensus algorithms to converge to a feasible solution, and then iteratively improves the allocation to approach the global optimal. Theoretical analysis for convergence and computational and communication complexity of the algorithm is included. This analysis is validated using representative simulation results including sensitivity studies for increasing the number of targets and varying network topologies.

Consensus Based Operating Picture for Distributed Battlefield Management

Developing a Common Operating Picture (COP) is a key enabler for the success on the modern battlefield. In this paper, we propose a distributed approach for developing a Consensus Based Common Operating Picture (CBCOP) where the participating assets iteratively synchronize their local operating pictures and establish a consensus. This enables generation of a COP in a truly distributed fashion with multiple command and control nodes each having a consistent COP and thereby mitigating some of the issues with centralized COP. The effectiveness of this strategy can only be realized by the development of algorithms for distributed situational awareness and mission planning. Thus we suggest two specific state of art algorithms and demonstrate their effectiveness in generating CBCOP through simulations.

Complexity Analysis of Spacecraft Architectures

In this paper, the authors explore the properties of different spacecraft architectures from the standpoint of system complexity. For this study, three architectures (monolithic, fractionated and modular) are chosen. A hypothetical mission is considered and spacecraft are designed using the three architectures and analyzed with regard to their system and design complexity. We represent each design as a network of component and interactions and measure the complexity of each design using network theory metrics, which show correlation with different aspects of system complexity. In conclusion, we discuss how the design features inherent in the architectures contribute to the system and design complexity.