Showing papers by "Anirban Mondal published in 2004"

P2PR-Tree: an R-tree-based spatial index for peer-to-peer environments

Abstract: The unprecedented growth and increased importance of geographically distributed spatial data has created a strong need for efficient sharing of such data Interestingly, the ever-increasing popularity of peer-to-peer (P2P) systems has opened exciting possibilities for such sharing This motivates our investigation into spatial indexing in P2P systems While much work has been done towards expediting search in file-sharing P2P systems, issues concerning spatial indexing in P2P systems are significantly more complicated due to overlaps between spatial objects and the complexity of spatial queries Incidentally, existing R-tree-based structures for distributed environments (e.g., the MC-Rtree) are not adequate for addressing the sheer scale, dynamism and heterogeneity of P2P environments Hence, we propose the P2PR-tree (Peer-to-Peer R-tree), which is a new spatial index specifically designed for P2P systems The main features of P2PR-tree are two-fold First, it is hierarchical and performs efficient pruning of the search space by maintaining minimal amount of information concerning peers that are far away and storing more information concerning nearby peers, thereby optimizing disk space usage Second, it is completely decentralized, scalable and robust to peers joining/leaving the system The results of our performance evaluation demonstrate that it is indeed practically feasible to share spatial data in a P2P system and that P2PR-tree is able to outperform MC-Rtree significantly.

On Improving the Performance Dependability of Unstructured P2P Systems via Replication

Abstract: The ever-increasing popularity of peer-to-peer (P2P) systems provides a strong motivation for designing a dependable P2P system. Dependability in P2P systems can be viewed from two different perspectives, namely system reliability (the availability of the individual peers) and system performance (data availability). This paper looks at dependability from the viewpoint of system performance and aims at enhancing the dependability of unstructured P2P systems via dynamic replication, while taking into account the disproportionately large number of ‘free riders’ that characterize P2P systems. Notably, the sheer size of P2P networks and the inherent heterogeneity and dynamism of the environment pose significant challenges to the improvement of dependability in P2P systems. The main contributions of our proposal are two-fold. First, we propose a dynamic data placement strategy involving data replication, the objective being to reduce the loads of the overloaded peers. Second, we present a dynamic query redirection technique which aims at reducing response times. Our performance evaluation demonstrates that our proposed technique is indeed effective in improving user response times significantly, thereby increasing the dependability of P2P systems.

On improving the performance dependability of unstructured P2P systems via replication

Abstract: The ever-increasing popularity of peer-to-peer (P2P) systems provides a strong motivation for designing a dependable P2P system. Dependability in P2P systems can be viewed from two different perspectives, namely system reliability (the availability of the individual peers) and system performance (data availability). This paper looks at dependability from the viewpoint of system performance and aims at enhancing the dependability of unstructured P2P systems via dynamic replication, while taking into account the disproportionately large number of 'free riders' that characterize P2P systems. Notably, the sheer size of P2P networks and the inherent heterogeneity and dynamism of the environment pose significant challenges to the improvement of dependability in P2P systems. The main contributions of our proposal are two-fold. First, we propose a dynamic data placement strategy involving data replication, the objective being to reduce the loads of the overloaded peers. Second, we present a dynamic query redirection technique which aims at reducing response times. Our performance evaluation demonstrates that our proposed technique is indeed effective in improving user response times significantly, thereby increasing the dependability of P2P systems.

Load-balancing remote spatial join queries in a spatial GRID

Abstract: The explosive growth of spatial data worldwide coupled with the emergence of GRID computing provides a strong motivation for designing a spatial GRID which allows transparent access to geographically distributed data. While different types of queries may be issued from any node in such a spatial GRID for retrieving the data stored at other (remote) nodes in the GRID, this paper specifically addresses spatial join queries. Incidentally, skewed user access patterns may cause a disproportionately large number of spatial join queries to be directed to a few ‘hot’ nodes, thereby resulting in severe load imbalance and consequently increased user response times. This paper focusses on load-balanced spatial join processing in a spatial GRID.

Load-balancing remote spatial join queries in a spatial GRID

Abstract: The explosive growth of spatial data worldwide coupled with the emergence of GRID computing provides a strong motivation for designing a spatial GRID which allows transparent access to geographically distributed data. While different types of queries may be issued from any node in such a spatial GRID for retrieving the data stored at other (remote) nodes in the GRID, this paper specifically addresses spatial join queries. Incidentally, skewed user access patterns may cause a disproportionately large number of spatial join queries to be directed to a few 'hot' nodes, thereby resulting in severe load imbalance and consequently increased user response times. This paper focusses on load-balanced spatial join processing in a spatial GRID.

On Spatial Indexing in Peer-to-Peer Environments

Abstract: unprecedented growth and increased importance of ge- ographically distributed spatial data has created a strong need for efficient sharing of such data among users. Interest- ingly, the ever-increasing popularity of peer-to-peer (P2P) systems has opened exciting possibilities for such sharing. This motivates our investigation into spatial indexing in P2P systems. While much work has been done towards expediting search in file-sharing P2P systems, issues con- cerning spatial indexing in P2P systems are significantly more complicated due to overlaps between spatial objects and the complexity of spatial queries. Incidentally, existing R-tree-based structures for distributed environments (e.g., the MC-Rtree) are not adequate for addressing the sheer scale, dynamism and heterogeneity of P2P environments. Hence, we propose P2PR-tree (Peer-to-Peer R-tree), which is a new R-tree-based indexing mechanism specifically for P2P systems. The main features of P2PR-tree are two-fold. First, it is hierarchical and performs efficient pruning of the search space by maintaining minimal amount of information concerning peers that are far away and storing more informa- tion concerning nearby peers, thereby optimizing disk space usage. Second, it is completely decentralized, scalable and robust to peers joining/leaving the system. The results of our performance evaluation demonstrate that it is indeed practically feasible to share spatial data in a P2P system and that P2PR-tree is able to outperform the MC-Rtree significantly.