Abstract:Recently, mobile computing has changed the way that spatial data and GIS are processed. Unlike wired and stand-alone GIS, now the trend has been switched from offline to real-time data processing using location aware services, such as GPS technology. The increased usage of location aware services in multiuser real-time environment has made transaction management incredibly significant. If the simultaneous query operations on the same data item are not handled intelligently then this results in data inconsisten… Show more
“…As discussed before, the tree-based indices have limitations such as unbalanced load, an overhead of locking the whole sub branch of tree, an overhead of excessive locking due to node overlap issue and dead space issue, an overhead of computationally expensive split/merge operations due to frequent location updates of moving objects. 26 In contrast to…”
Section: Background and Literature Reviewmentioning
confidence: 92%
“…This is because the concurrent operations accessing the data simultaneously for read-only purpose will not make any changes to the data and thus the access will F I G U R E 6 Linear hashing. 26 be safe. However, in exclusive mode, once an exclusive lock is acquired by any operation against a shared resource, then it cannot be accessed by any other operation.…”
Section: Lock-based Concurrency Control and Corresponding Consistent ...mentioning
confidence: 96%
“…Each category of concurrency control protocol has some pros and cons at broader level. The pros and cons have been highlighted and discussed in Reference 26. Lock‐based solutions provide best consistency and serializability but are not preferred for query intensive applications.…”
Section: Problem Descriptionmentioning
confidence: 99%
“…Likewise, there are many concurrency control protocols proposed in the literature for mobile environment. A detailed analysis and comparison of such protocols has been made in Reference 26. However, our focus is on designing of consistent index for moving objects not just a concurrency control algorithm.…”
Section: Background and Literature Reviewmentioning
confidence: 99%
“…But, tree‐based indices have limitations such as unbalanced load, an overhead of locking the whole sub branch of tree, an overhead of excessive locking due to node overlap issue and dead space issue, an overhead of computationally expensive split/merge operations due to frequent location updates of moving objects. These challenges are discussed and analyzed in detail in Reference 26. In contrast to it, hash‐based solutions result into balanced load that result in uniform distribution of records.…”
SummaryDue to recent developments in location‐based services and mobile computing, the need for indices for moving objects has been strengthened to improve the response time of a query operation. With a single index in place for managing both the update and query operations for moving objects, the index needs to be updated each time the object moves. This deteriorates the performance of concurrent query operations. It is critical to handle the conflicts between continuous update and query operations effectively using appropriate concurrency control protocol otherwise, inconsistent results will be reported. Many indices have been proposed in the literature for moving objects but they lack the support for processing concurrent operations. Further, the consistent indices in the literature are based on tree structure that have computationally expensive split/merge operations that can negatively affect the response time of query processing algorithms. Moreover such tree based indices are proposed for historical and future timeline data. As the scope of this article is on current timeline and concurrent continuous query operations, therefore, we exploit state of the art hash‐based indices in the literature and presented the two consistent versions. The comparative analysis of the indices is performed and meaningful findings are also presented along.
“…As discussed before, the tree-based indices have limitations such as unbalanced load, an overhead of locking the whole sub branch of tree, an overhead of excessive locking due to node overlap issue and dead space issue, an overhead of computationally expensive split/merge operations due to frequent location updates of moving objects. 26 In contrast to…”
Section: Background and Literature Reviewmentioning
confidence: 92%
“…This is because the concurrent operations accessing the data simultaneously for read-only purpose will not make any changes to the data and thus the access will F I G U R E 6 Linear hashing. 26 be safe. However, in exclusive mode, once an exclusive lock is acquired by any operation against a shared resource, then it cannot be accessed by any other operation.…”
Section: Lock-based Concurrency Control and Corresponding Consistent ...mentioning
confidence: 96%
“…Each category of concurrency control protocol has some pros and cons at broader level. The pros and cons have been highlighted and discussed in Reference 26. Lock‐based solutions provide best consistency and serializability but are not preferred for query intensive applications.…”
Section: Problem Descriptionmentioning
confidence: 99%
“…Likewise, there are many concurrency control protocols proposed in the literature for mobile environment. A detailed analysis and comparison of such protocols has been made in Reference 26. However, our focus is on designing of consistent index for moving objects not just a concurrency control algorithm.…”
Section: Background and Literature Reviewmentioning
confidence: 99%
“…But, tree‐based indices have limitations such as unbalanced load, an overhead of locking the whole sub branch of tree, an overhead of excessive locking due to node overlap issue and dead space issue, an overhead of computationally expensive split/merge operations due to frequent location updates of moving objects. These challenges are discussed and analyzed in detail in Reference 26. In contrast to it, hash‐based solutions result into balanced load that result in uniform distribution of records.…”
SummaryDue to recent developments in location‐based services and mobile computing, the need for indices for moving objects has been strengthened to improve the response time of a query operation. With a single index in place for managing both the update and query operations for moving objects, the index needs to be updated each time the object moves. This deteriorates the performance of concurrent query operations. It is critical to handle the conflicts between continuous update and query operations effectively using appropriate concurrency control protocol otherwise, inconsistent results will be reported. Many indices have been proposed in the literature for moving objects but they lack the support for processing concurrent operations. Further, the consistent indices in the literature are based on tree structure that have computationally expensive split/merge operations that can negatively affect the response time of query processing algorithms. Moreover such tree based indices are proposed for historical and future timeline data. As the scope of this article is on current timeline and concurrent continuous query operations, therefore, we exploit state of the art hash‐based indices in the literature and presented the two consistent versions. The comparative analysis of the indices is performed and meaningful findings are also presented along.
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