Srinivasa S. Vulli

Bio: Srinivasa S. Vulli is an academic researcher from Missouri University of Science and Technology. The author has contributed to research in topics: Static routing & Destination-Sequenced Distance Vector routing. The author has an hindex of 3, co-authored 4 publications receiving 67 citations. Previous affiliations of Srinivasa S. Vulli include University of Missouri–Kansas City.

Dynamic Social Grouping Based Routing in a Mobile Ad-hoc Network

Abstract: The patterns of movement used by Mobile Ad-Hoc networks are application specific, in the sense that networks use nodes which travel in different paths. When these nodes are used in experiments involving social patterns, such as wildlife tracking, algorithms which detect and use these patterns can be used to improve routing efficiency. The intent of this paper is to introduce a routing algorithm which forms a series of social groups which accurately indicate a node’s regular contact patterns while dynamically shifting to represent changes to the social environment. With the social groups formed, a probabilistic routing schema is used to effectively identify which social groups have consistent contact with the base station, and route accordingly. The algorithm can be implemented dynamically, in the sense that the nodes initially have no awareness of their environment, and works to reduce overhead and message traffic while maintaining high delivery ratio.

Dynamic social grouping based routing in a Mobile Ad-Hoc network

Abstract: The patterns of movement used by Mobile Ad-Hoc networks are application specific, in the sense that networks use nodes which travel in different paths. When these nodes are used in experiments involving social patterns, such as wildlife tracking, algorithms which detect and use these patterns can be used to improve routing efficiency. The intent of this paper is to introduce a routing algorithm which forms a series of social groups which accurately indicate a node's regular contact patterns while dynamically shifting to represent changes to the social environment. With the social groups formed, a probabilistic routing schema is used to effectively identify which social groups have consistent contact with the base station, and route accordingly. The algorithm can be implemented dynamically, in the sense that the nodes initially have no awareness of their environment, and works to reduce overhead and message traffic while maintaining high delivery ratio.

Social group detection based routing in Delay Tolerant Networks

Abstract: When implementing Mobile Ad Hoc Networks, a key characteristic of the network is the mobility pattern of the nodes. Based on the application, nodes can follow semi-predictable patterns, such as the routes followed by Vehicular Ad Hoc Networks, or the more strict schedules followed by aerial reconnaissance. Optimal routing schemes tend to take advantage of information regarding these patterns. In social environments, such as wildlife tracking or sending messages between humans, the devices and/or users will follow regular contact habits, tending to encounter social groups in which they participate. By identifying these groups, the patterns are used to optimize routing through a social environment. Dynamic Social Grouping (DSG), used to route messages strictly from a node to a basestation, is ideal for gathering sensor data and updating a shared data cache. In contrast, Dynamic Social Grouping-Node to Node (DSG-N2) is used to route messages between nodes, generally conventional communications. Both of these algorithms can be implemented ad null, meaning the devices initially have no information about their environment, and they work to reduce bandwith and delivery time while maintaining a high delivery ratio. In addition to presenting these two routing schemas, this article compares and contrasts two methods for estimating nodes' delivery probabilities. The Contact Based Probability is based on encounters with other nodes, and the Performance Based Probability is based on the behavior of previous messages. The probability estimates were then validated with the Oracle analysis, which is based on knowledge of future events. This analysis indicated that DSG-N2 probability estimates are comparable to the ideal.

Individual-based artificial ecosystems for design and optimization

Abstract: Individual-based modeling has gained popularity over the last decade, mainly due to its proven ability to address a variety of problems, including modeling complex systems from bottom-up, providing relationships between component level and system level parameters, and relating emergent system level behaviors from simple component level interactions. Availability of computational power to run simulation models with thousands to millions of agents is another driving force in the wide-spread adoption of individual-based modeling. In this paper, we propose an individual-based modeling approach to solve engineering design and optimization problems using artificial ecosystems (AES). The problem to be solved is "mapped" to an appropriate AES consisting of an environment and one or more evolving species. The AES is then allowed to evolve. The optimal solution emerges through the interactions of individuals amongst themselves and their environment. The fitness function or selection mechanism is internal to the ecosystem and is based on the interactions between individuals, which makes the proposed approach attractive for design and optimization in complex systems, where formulation of a global fitness function is often complicated. The efficacy of the proposed approach is demonstrated using the problem of parameter estimation for binary texture synthesis.

Applications, Architectures, and Protocol Design Issues for Mobile Social Networks: A Survey

Abstract: The mobile social network (MSN) combines techniques in social science and wireless communications for mobile networking The MSN can be considered as a system which provides a variety of data delivery services involving the social relationship among mobile users This paper presents a comprehensive survey on the MSN specifically from the perspectives of applications, network architectures, and protocol design issues First, major applications of the MSN are reviewed Next, different architectures of the MSN are presented Each of these different architectures supports different data delivery scenarios The unique characteristics of social relationship in MSN give rise to different protocol design issues These research issues (eg, community detection, mobility, content distribution, content sharing protocols, and privacy) and the related approaches to address data delivery in the MSN are described At the end, several important research directions are outlined

Exploiting social ties for cooperative D2D communications: a mobile social networking case

Abstract: Thanks to the convergence of pervasive mobile communications and fast-growing online social networking, mobile social networking is penetrating into our everyday life. Aiming to develop a systematic understanding of mobile social networks, in this paper we exploit social ties in human social networks to enhance cooperative device-to-device (D2D) communications. Specifically, as handheld devices are carried by human beings, we leverage two key social phenomena, namely social trust and social reciprocity, to promote efficient cooperation among devices. With this insight, we develop a coalitional game-theoretic framework to devise social-tie-based cooperation strategies for D2D communications. We also develop a network-assisted relay selection mechanism to implement the coalitional game solution, and show that the mechanism is immune to group deviations, individually rational, truthful, and computationally efficient. We evaluate the performance of the mechanism by using real social data traces. Simulation results corroborate that the proposed mechanism can achieve significant performance gain over the case without D2D cooperation.

A Survey on Mobile Social Networks: Applications, Platforms, System Architectures, and Future Research Directions

Abstract: Mobile social networks (MSNs) have become increasingly popular in supporting many novel applications since emerging in the recent years. Their applications and services are of great interest to service providers, application developers, and users. This paper distinguishes MSNs from conventional social networks and provides a comprehensive survey of MSNs with regard to platforms, solutions, and designs of the overall system architecture. We review the popular MSN platforms and experimental solutions for existing MSN applications and services and present the dominant mobile operating systems on which MSNs are implemented. We then analyze and propose the overall architectural designs of conventional and future MSN systems. In particular, we present the architectural designs from two perspectives: from the client side to the server side, and from the wireless data transmission level to the terminal utilization level. We further introduce and compare the unique features, services, and key technologies of two generations of architectural designs of MSN systems. Then, we classify the existing MSN applications and propose one special form of MSN, i.e., vehicular social network, and demonstrate its unique features and challenges compared with common MSNs. Finally, we summarize the major challenges for on-going MSN research and outline possible future research directions.

Limits of predictability in human mobility

Abstract: A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: To what degree is human behavior predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual's trajectory, we find a 93% potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, which is largely independent of the distance users cover on a regular basis.

Socially Aware Energy-Efficient Mobile Edge Collaboration for Video Distribution

Abstract: To relieve the current overload of cellular networks caused by the continuously growing multimedia service, mobile edge collaboration, which exploits edge users to distribute videos for base station (BS), provides an effective way to share the heavy BS load. With the emergence of mobile edge technologies for Internet-of-Things applications, such as device to device and machine to machine, how to exploit users’ social characteristics and mobility to minimize the number of transmissions of BS and how to improve the quality of experience of users have become the key challenges. In this paper, we study two aspects that are critical to these issues. One is the two-step detection mechanism, namely the establishment of virtual communities and collaborative clusters. Specifically, we take into consideration user preference for content and location. First of all, a virtual community is established, which exploits the coalition game based on the user's preference list to dynamically divide users into multiple communities. Then, to take full advantage of the temporary link established between users, a grid-based clustering method is proposed to manage the video requesting users. On the other hand, we propose a scalable video coding sharing scheme based on user's social attributes. This approach makes video distribution more flexible at the edge of mobile network through collaboration among users, and effectively reduces transmission energy consumption of transmitters. Numerical results show that the proposed mechanism can not only effectively alleviate the BS load, but also dramatically improve the reliability and adaptability of video distribution.