Collaborative Caching for Energy Optimization in Content-Centric Internet of Things

Wang, Shupeng; Chen, Handi; Wang, Yongjian

doi:10.1109/tcss.2021.3087197

Cited by 17 publications

(6 citation statements)

References 38 publications

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“…Additionally, caching content at all network nodes can result in increased unwanted cache usage and unnecessary consumption of network resources. The Client Cache Strategy (CCS) [28] improves content validity by determining content popularity based on requests received at network nodes. However, this process can be timeconsuming and reduce caching performance in terms of content retrieval latency and cache hit.…”

Section: Related Studiesmentioning

confidence: 99%

Performance Measurement Through Caching in Named Data Networking Based Internet of Things

Naeem

Ahmad

2023

IEEE Access

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Named Data Networking (NDN) is considered the future of Internet architecture, providing a realistic solution for data delivery using a caching module in an Internet of Things (IoT) based environment. However, a major challenge of the caching module is data redundancy, which decreases the overall caching performance by caching similar data at numerous locations in an NDN-based IoT scenario. Moreover, the latency and stretch are maximized due to high redundant caching operations. Several attempts have been made by the research community to provide an enhanced solution to overcome such issues. However, the caching module still requires efficient enhancement. This study provides critical insights into earlier caching strategies. To solve the problems of these caching strategies, an enhanced caching strategy is proposed, named Priority-based Content Popularity-Aware (PCPA) Caching Strategy, which is evaluated by comparing its performance with some of the novel NDN-based IoT caching strategies. The proposed caching strategy outperforms the comparing strategies in terms of latency, hop count, cache hit ratio and energy consumption.

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Section: Related Studiesmentioning

confidence: 99%

Performance Measurement Through Caching in Named Data Networking Based Internet of Things

Naeem

Ahmad

2023

IEEE Access

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“…Note that CSC is not designed to replace existing caching schemes but can be implemented as a complementary part to improve the performance of existing caching schemes. We implement CSC on the top of several caching schemes including MPC [14], CPCCS [15], and CCS [16], namely CSC-MPC, CSC-CPCCS, and CSC-CCS. It does mean that CSC works on the popularity ranking mechanism and resource management of MPC, CPCCS, and CCS, while it adds a module for efficient CS information exchange and improves the network performance by coordinating the CS of nodes in their neighborhood.…”

Section: Simulation and Configurationmentioning

confidence: 99%

“…It does mean that CSC works on the popularity ranking mechanism and resource management of MPC, CPCCS, and CCS, while it adds a module for efficient CS information exchange and improves the network performance by coordinating the CS of nodes in their neighborhood. We conduct experimental performance evaluation of the proposed caching policy compared to state-of-the-art caching schemes, MPC [14], CPCCS [15], and CCS [16]. Figure 1 shows average cache hit ratio results obtained with MPC, CPCCS, and CCS in cases with and without CSC.…”

Section: Simulation and Configurationmentioning

confidence: 99%

“…Note that CSC is not designed to replace existing caching schemes but can be implemented as a complementary part to improve the performance of existing caching schemes. We implement CSC on the top of state-of-the-art popularity-based caching schemes including MPC [14], CPCCS [15], and CCS [16], namely CSC-MPC, CSC-CPCCS, and CSC-CCS. Through analysis and experiments, we show that the proposed caching policy achieves a significant improvement in terms of cache hit ratio, stretch ratio, content retrieval latency and energy efficiency significantly compared to state-of-the-art schemes.…”

Section: Introductionmentioning

confidence: 99%

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An Efficient Distributed Content Store-Based Caching Policy for Information-Centric Networking

Dinh

Kim

2022

Sensors

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Content store (CS) is one of the main components of information-centric networking (ICN), which enables content objects to be cached and retrieved from any intermediate node in the network. However, in existing ICN designs, CS information is not exploited to coordinate content caching and content retrieval. CS of nodes in the network operates independently while Interest packets forwarding mainly uses forwarding information base (FIB). This paper highlights the importance of CS information for efficient content caching and content retrieval to improve the performance of information-centric networking, especially in resource-constrained environments like the Internet of Things. We propose an efficient caching policy to coordinate the CS of a node with its neighbor nodes in a distributed manner so that more and more popular content objects are cached in the neighborhood of the node. To exploit and coordinate CS information among nodes, we urge to enable CS information in the data plane of the network and design an efficient way for CS information transmission. Each node contributes to the objective of its neighborhood by maximizing its number of unique popular content objects being cached in its CS and not cached in the CS of its neighbors. We implement the proposed policy on top of state-of-the-art popularity-based caching schemes. Through analysis and experiments, we show that the proposed caching policy achieves a significant improvement in terms of cache hit ratio, stretch ratio, content retrieval latency, and energy efficiency significantly compared to state-of-the-art schemes.

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“…In recent years, Internet of Things (IoT) technology has been applied to a wide range of applications [1,2], mainly driven by the rising number of Internet-connected devices that already amount to several billion [3]. The devices of IoT [4] aim to connect everyday objects, such as humans, plants, and even animals, to the Internet to enable interactions among these objects [5].…”

Section: Introductionmentioning

confidence: 99%

H2SA-ALSH: A Privacy-Preserved Indexing and Searching Schema for IoT Data Collection and Mining

Zhu

et al. 2022

Wireless Communications and Mobile Computing

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Currently, smart devices of Internet of Things generate massive amount of data for different applications. However, it will expose sensitive information to external users in the process of IoT data collection, transmission, and mining. In this paper, we propose a novel indexing and searching schema based on homocentric hypersphere and similarity-aware asymmetric LSH (H2SA-ALSH) for privacy-preserved data collection and mining over IoT environments. The H2SA-ALSH collects multidimensional data objects and indexes their features according to the Euclidean norm and cosine similarity. Additionally, we design a c - k -AMIP searching algorithm based on H2SA-ALSH. Our approach can boost the performance of the maximum inner production (MIP) queries and top- k queries for a given query vector using the proposed indexing schema. Experiments show that our algorithm is excellent in accuracy and efficiency compared with other ALSH-based algorithms using real-world datasets. At the same time, our indexing scheme can protect the user’s privacy via generating similarity-based indexing vectors without exposing raw data to external users.

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Collaborative Caching for Energy Optimization in Content-Centric Internet of Things

Cited by 17 publications

References 38 publications

Performance Measurement Through Caching in Named Data Networking Based Internet of Things

Performance Measurement Through Caching in Named Data Networking Based Internet of Things

An Efficient Distributed Content Store-Based Caching Policy for Information-Centric Networking

H2SA-ALSH: A Privacy-Preserved Indexing and Searching Schema for IoT Data Collection and Mining

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