DiSCO: A Distributed Semantic Cache Overlay for Location-Based Services

Lübbe, Carlos; Brodt, Andreas; Cipriani, Nazario; Großmann, Matthias; Mitschang, Bernhard

doi:10.1109/mdm.2011.56

Cited by 10 publications

(4 citation statements)

References 15 publications

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“…As this paper builds upon the ideas of previous work (Lübbe et al, 2011;Lübbe et al, 2012;Lübbe et al, 2013), this section outlines their major contributions. First, we describe the general architecture of the distributed main memory cache.…”

Section: Foundationsmentioning

confidence: 99%

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An Elastic Cache Infrastructure through Multi-level Load-balancing

Lübbe

Mitschang

2013

Proceedings of the 2nd International Conference on Data Technologies and Applications

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An increasing demand for geographic data compels data providers to handle an enormous amount of range queries at their data tier. In answer to this, frequently used data can be cached in a distributed main memory store in which the load is balanced among multiple cache nodes. To make appropriate load-balancing decisions, several key-indicators such as expected and actual workload as well as data skew can be used. In this work, we make use of an abstract mathematical model to consolidate these indicators. Moreover, we propose a multi-level load-balancing algorithm which considers the different indicators in separate stages. Our evaluation shows that our multi-level approach significantly improves the resource utilization in comparison to existing technology.

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Section: Foundationsmentioning

confidence: 99%

“…Overview. (Lübbe et al, 2011) introduced data structures and algorithms to store spatial data on a single node. The work bases on a general data model comprising objects which contain an obligatory attribute delineating the spatial extend of the object and arbitrary additional non-spatial attributes.…”

Section: Foundationsmentioning

confidence: 99%

An Elastic Cache Infrastructure through Multi-level Load-balancing

Lübbe

Mitschang

2013

Proceedings of the 2nd International Conference on Data Technologies and Applications

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“…This section, briefly sketches the basic concepts of our previous work [5], [7] which lay the foundation of this work. We refer the reader to these papers for any details.…”

Section: Foundationsmentioning

confidence: 99%

“…In [7], we present the general architecture of a distributed spatial main memory cache, where multiple cache nodes collaborate to provide highly scalable access to frequently used data. Figure 1a depicts the general architecture of such a system.…”

Section: Foundationsmentioning

confidence: 99%

Holistic Load-Balancing in a Distributed Spatial Cache

Lübbe

Mitschang

2013

2013 IEEE 14th International Conference on Mobile Data Management

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A steadily growing number of people using location based services (LBS) inflict massive query loads on the data tier of an LBS. As such queries usually possess considerable overlap, multiple cache nodes collaborating in a distributed spatial cache can provide scalable access to frequently used data. To preserve high throughput throughout the complete execution process, it is necessary to balance the accumulating load among the participating cache nodes. In this work, we identify three key-indicators to improve resource utilization during the load-balancing process: data skew, anticipated data access patterns and dynamic load peaks. For this reason, we introduce a comprehensive mathematical model to express the key-indicators as probability distribution functions. We fuse the different key-indicators into a single holistic distribution model. In the course of this, we devise a methodology from our holistic distribution model towards a distributed spatial cache offering improved load-balancing facilities.

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RSCVC: Row‐based semantic cache with incremental versioning consistency

Yang

Zhang

et al. 2020

Concurrency and Computation

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SummaryIn the mobile computing environment, how to make the data access more efficient is a challenge due to the narrow communication bandwidth, the frequent disconnections of network, and the limited resources. Therefore, it is necessary to cache data on the client side. Besides, a good cache consistency method is essential to ensure the correctness. In this article, a row‐based semantic cache with incremental versioning consistency (RSCVC) is proposed. In RSCVC, we designed a semantic cache algorithm, a query trimming and optimizing algorithm, and a version‐based consistency strategy. This RSCVC cache mainly has two advantages. On one hand, it can obviously improve the response time of query and the hit ratio of the cache. On the other hand, the version‐based consistency enhances the stability of the system especially in high‐concurrency situations. Experiments demonstrate the efficacy of our proposed method and its superiority to state‐of‐the‐art methods.

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DiSCO: A Distributed Semantic Cache Overlay for Location-Based Services

Cited by 10 publications

References 15 publications

An Elastic Cache Infrastructure through Multi-level Load-balancing

An Elastic Cache Infrastructure through Multi-level Load-balancing

Holistic Load-Balancing in a Distributed Spatial Cache

RSCVC: Row‐based semantic cache with incremental versioning consistency

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