Aditya Kurve | Penn State University (original) (raw)

Papers by Aditya Kurve

Crowdsourcing allows instant recruitment of workers on the web to annotate image, webpage, or doc... more Crowdsourcing allows instant recruitment of workers on the web to annotate image, webpage, or document databases. However, worker unreliability prevents taking a worker's responses at “face value”. Thus, responses from multiple workers are typically aggregated to more reliably infer ground-truth answers. We study two approaches for crowd aggregation on multicategory answer spaces: stochastic modeling-based and deterministic objective function-based. Our stochastic model for answer generation plausibly captures the interplay between worker skills, intentions, and task difficulties and captures a broad range of worker types. Our deterministic objective-based approach aims to maximize the average aggregate confidence of weighted plurality crowd decision making. In both approaches, we explicitly model the skill and intention of individual workers, which is exploited for improved crowd aggregation. Our methods are applicable in both unsupervised and semi-supervised settings, and also when the batch of tasks is heterogeneous, i.e., from multiple domains, with task-dependent answer spaces. As observed experimentally, the proposed methods can defeat “tyranny of the masses”, i.e., they are especially advantageous when there is an (a priori unknown) minority of skilled workers amongst a large crowd of unskilled (and malicious) workers.

Abstract Network model partitioning is a key component of distributed network simulations. Simula... more Abstract Network model partitioning is a key component of distributed network simulations. Simulations slow down considerably due to inequitable load balancing and heavy inter-host communication leading to unbounded synchronization overhead. Also, regularly refreshing the node partition is necessary due to to the dynamic nature of simulation load and event generation. In this paper, we propose a distributed method for network partitioning which includes a coarse initial partitioning followed by iterative improvements in the partition. We ...

The performance of an optimistic parallel discrete event simulator (PDES) in terms of the total s... more The performance of an optimistic parallel discrete event simulator (PDES) in terms of the total simulation execution time of an experiment depends on a large set of variables. Many of them have a complex and generally unknown relationship with the simulation execution time. In this paper, we describe an agent-based performance model of a PDES kernel that is typically used to simulate large-sized complex networks on multiple processors or machines. The agent-based paradigm greatly simplifies the modeling of system dynamics by representing a component logical process (LP) as an autonomous agent that interacts with other LPs through event queues and also interacts with its environment which comprises the processor it resides on. We model the agents representing the LPs using an abstract "base" class of an LP agent that allows us to use a generic behavioral model of an agent that can be inherited by more specific derived classes. The base class focuses only on the details that most likely influence the overall simulation execution time of the experiment. Using this model, we evaluate a novel local incentive based partitioning algorithm where each LP makes an informed local decision about its assignment

A super-peer based overlay network architecture for peer-to-peer (P2P) systems allows for some no... more A super-peer based overlay network architecture for peer-to-peer (P2P) systems allows for some nodes, known as the super-peers, that are more resourceendowed than others, to assume a higher share of workload. Ordinary peers are connected to the super-peers and rely on them for their transactional needs. Many criteria for a peer to choose its super-peer have been explored, some of them based on physical proximity, semantic proximity, or by purely random choice. In this paper, we propose an incentive-based criterion that uses semantic similarities between the content interests of the peers and, at the same time, encourages even load distribution across the super-peers. The incentive is achieved via a game theoretic framework that considers each peer as a rational player, allowing stable Nash equilibria to exist and hence guarantees a fixed point in the strategy space of the peers. This guarantees convergence (assuming static network parameters) to a locally optimal assignment of peers to super-peers with respect to a global cost that approximates the average query resolution time. We also show empirically that the local cost framework that we employ performs closely to (and in some cases better than) a similar scheme based on the formulation of a centralized cost function that requires the peers to know an additional global parameter.

… of the 2011 International Workshop on …, Jan 1, 2011

arXiv preprint arXiv:1111.0875, Jan 1, 2011

Communications (ICC), 2011 IEEE …, Jan 1, 2011

Decentralized reputation systems help to enforce discipline and fairness in large unstructured an... more Decentralized reputation systems help to enforce discipline and fairness in large unstructured and ad-hoc systems by rewarding good behavior and penalizing dishonest or greedy behavior. They are essential in large networks of independent nodes where centralized monitoring of node behavior is difficult due to the sheer size of the network. Sybil nodes pose a threat to the reputation systems by false referrals through sybil identities. We propose a scalable and distributed algorithm to identify attack edges and quarantine sybil clusters. This algorithm works well with dynamic trust graphs as nodes do not need to store any pre-computed data.

Potentials, IEEE, Jan 1, 2009

V ery few technologies have had as much impact on the trajectory of evolution of wireless communi... more V ery few technologies have had as much impact on the trajectory of evolution of wireless communication systems as Multiple Input Multiple Output (MIMO) systems. MIMO systems have already been employed in the existing 802.11n and 802.16e standards resulting in a huge leap in their achievable rates. A relatively recent idea of extending the benefits of MIMO systems to multi-user scenarios seems promising in the context of achieving high data rates envisioned for future cellular standards after 3G. Although substantial research has been done on the theoretical front, recent focus is on making multi user MIMO (MU-MIMO) practically realizable. It offers an enormous scope for further research in the coming years. As in the case of any evolving technology in communication systems, the literature concerning MU-MIMO systems involves complex mathematical analysis, making it difficult for an ordinary reader to comprehend. This article aims at giving an insight into MU-MIMO systems-its concept, fundamentals, and trends including an overview of important research results. It is intended at giving a good start to amateurs interested in being part of the community that shapes the future of wireless systems.

Crowdsourcing allows instant recruitment of workers on the web to annotate image, webpage, or doc... more Crowdsourcing allows instant recruitment of workers on the web to annotate image, webpage, or document databases. However, worker unreliability prevents taking a worker's responses at “face value”. Thus, responses from multiple workers are typically aggregated to more reliably infer ground-truth answers. We study two approaches for crowd aggregation on multicategory answer spaces: stochastic modeling-based and deterministic objective function-based. Our stochastic model for answer generation plausibly captures the interplay between worker skills, intentions, and task difficulties and captures a broad range of worker types. Our deterministic objective-based approach aims to maximize the average aggregate confidence of weighted plurality crowd decision making. In both approaches, we explicitly model the skill and intention of individual workers, which is exploited for improved crowd aggregation. Our methods are applicable in both unsupervised and semi-supervised settings, and also when the batch of tasks is heterogeneous, i.e., from multiple domains, with task-dependent answer spaces. As observed experimentally, the proposed methods can defeat “tyranny of the masses”, i.e., they are especially advantageous when there is an (a priori unknown) minority of skilled workers amongst a large crowd of unskilled (and malicious) workers.

Abstract Network model partitioning is a key component of distributed network simulations. Simula... more Abstract Network model partitioning is a key component of distributed network simulations. Simulations slow down considerably due to inequitable load balancing and heavy inter-host communication leading to unbounded synchronization overhead. Also, regularly refreshing the node partition is necessary due to to the dynamic nature of simulation load and event generation. In this paper, we propose a distributed method for network partitioning which includes a coarse initial partitioning followed by iterative improvements in the partition. We ...

The performance of an optimistic parallel discrete event simulator (PDES) in terms of the total s... more The performance of an optimistic parallel discrete event simulator (PDES) in terms of the total simulation execution time of an experiment depends on a large set of variables. Many of them have a complex and generally unknown relationship with the simulation execution time. In this paper, we describe an agent-based performance model of a PDES kernel that is typically used to simulate large-sized complex networks on multiple processors or machines. The agent-based paradigm greatly simplifies the modeling of system dynamics by representing a component logical process (LP) as an autonomous agent that interacts with other LPs through event queues and also interacts with its environment which comprises the processor it resides on. We model the agents representing the LPs using an abstract "base" class of an LP agent that allows us to use a generic behavioral model of an agent that can be inherited by more specific derived classes. The base class focuses only on the details that most likely influence the overall simulation execution time of the experiment. Using this model, we evaluate a novel local incentive based partitioning algorithm where each LP makes an informed local decision about its assignment

A super-peer based overlay network architecture for peer-to-peer (P2P) systems allows for some no... more A super-peer based overlay network architecture for peer-to-peer (P2P) systems allows for some nodes, known as the super-peers, that are more resourceendowed than others, to assume a higher share of workload. Ordinary peers are connected to the super-peers and rely on them for their transactional needs. Many criteria for a peer to choose its super-peer have been explored, some of them based on physical proximity, semantic proximity, or by purely random choice. In this paper, we propose an incentive-based criterion that uses semantic similarities between the content interests of the peers and, at the same time, encourages even load distribution across the super-peers. The incentive is achieved via a game theoretic framework that considers each peer as a rational player, allowing stable Nash equilibria to exist and hence guarantees a fixed point in the strategy space of the peers. This guarantees convergence (assuming static network parameters) to a locally optimal assignment of peers to super-peers with respect to a global cost that approximates the average query resolution time. We also show empirically that the local cost framework that we employ performs closely to (and in some cases better than) a similar scheme based on the formulation of a centralized cost function that requires the peers to know an additional global parameter.

… of the 2011 International Workshop on …, Jan 1, 2011

arXiv preprint arXiv:1111.0875, Jan 1, 2011

Communications (ICC), 2011 IEEE …, Jan 1, 2011

Decentralized reputation systems help to enforce discipline and fairness in large unstructured an... more Decentralized reputation systems help to enforce discipline and fairness in large unstructured and ad-hoc systems by rewarding good behavior and penalizing dishonest or greedy behavior. They are essential in large networks of independent nodes where centralized monitoring of node behavior is difficult due to the sheer size of the network. Sybil nodes pose a threat to the reputation systems by false referrals through sybil identities. We propose a scalable and distributed algorithm to identify attack edges and quarantine sybil clusters. This algorithm works well with dynamic trust graphs as nodes do not need to store any pre-computed data.

Potentials, IEEE, Jan 1, 2009

V ery few technologies have had as much impact on the trajectory of evolution of wireless communi... more V ery few technologies have had as much impact on the trajectory of evolution of wireless communication systems as Multiple Input Multiple Output (MIMO) systems. MIMO systems have already been employed in the existing 802.11n and 802.16e standards resulting in a huge leap in their achievable rates. A relatively recent idea of extending the benefits of MIMO systems to multi-user scenarios seems promising in the context of achieving high data rates envisioned for future cellular standards after 3G. Although substantial research has been done on the theoretical front, recent focus is on making multi user MIMO (MU-MIMO) practically realizable. It offers an enormous scope for further research in the coming years. As in the case of any evolving technology in communication systems, the literature concerning MU-MIMO systems involves complex mathematical analysis, making it difficult for an ordinary reader to comprehend. This article aims at giving an insight into MU-MIMO systems-its concept, fundamentals, and trends including an overview of important research results. It is intended at giving a good start to amateurs interested in being part of the community that shapes the future of wireless systems.