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The substantial surge in users has adversely impacted the performance of the present IP-based Internet. Named data networking (NDN) emerges as a future alternative, given its distributed content caching system, where data can be cached in multiple routers and retrieved from the closest one instead of the original producer, enhancing content availability, reducing latency, and minimizing data loss. This paper introduces the less popular content eviction (LPCE) policy, a novel cache replacement scheme designed to enhance the caching performance of the conventional LFU (least frequently used) policy in NDN routers, thereby improving overall network efficiency. The proposed method subsumes LFU and FIFO (first in first out) policies and employs an additional list controlled by the LRU (least recently used) policy. Utilizing the ccnSim simulator, we conduct a comparison of LPCE’s performance with that of the LFU technique and other competing caching techniques, considering variations in several simulation parameters. Experimental results reveal that the proposed LPCE algorithm excels over others across a majority of performance metrics, such as cache hit ratio, content delivery delay, upstream hop count, network traffic, and producers’ load. Besides, the findings indicate that LPCE outperforms LFU, with an increase in cache hit ratio ranging from 1.32% to 5.75%. [ABSTRACT FROM AUTHOR]

Modern intelligent buildings should be designed to provide comfort and optimal quality of life for occupants. Therefore, smart home devices that allow for the control of actual indoor ambience, which is critical to minimizing dissatisfaction, and simultaneously reduce the energy consumption must be modeled. In this paper, we propose an original model of the contribution of objects, where each object contributes to a type of ambience, namely, thermal, visual, acoustic and air quality. In other words, a given indoor ambience is defined by the contribution of objects. The discrete event system specification (DEVS) is a formalism for describing simulation models in a modular way. The modular nature of the DEVS formalism is exploited in this study by forming submodels of smart objects that allow domain experts to develop simulation techniques independently and later combine their work for reducing energy consumption and improving comfort. We have incorporated fuzzy reasoning methods in the DEVS formalism to account for the human perception error in an indoor environment, allowing for improved indoor environmental quality management in buildings. [ABSTRACT FROM AUTHOR]