Information-centric networking (ICN) is a promising architecture and has attracted much attention in the area of future Internet architectures. As one of the key technologies in ICN, in-network caching can enhance content retrieval at a global scale without requiring any special infrastructure. In this paper, we propose a workload-aware caching policy, LRU-GT, which allows cache nodes to protect newly cached contents for a period of time (guard time) during which contents are protected from being replaced. LRU-GT can utilize the temporal locality and distinguish contents of different popularity, which are both the characteristics of the workload. Cache replacement is modeled as a semi-Markov process under the Independent Reference Model (IRM) assumption and a theoretical analysis proves that popular contents have longer sojourn time in the cache compared with unpopular ones in LRU-GT and the value of guard time can affect the cache hit ratio. We also propose a dynamic guard time adjustment algorithm to optimize the performance. Simulation results show that LRU-GT can reduce the average hops to get contents and improve cache hit ratio.

We propose a dynamic voltage scaling algorithm to exploit the temporal locality called TLDVS (Temporal Locality DVS) that can achieve significant energy savings while simultaneously preserving timeliness guarantees made by real-time scheduling. Traditionally hard real-time scheduling algorithms assume that the actual computation requirement of tasks would be varied continuously from time to time, but most real-time tasks have a limited number of operational modes changing with temporal locality. Such temporal locality can be exploited for energy savings by scaling down the operating frequency and the supply voltage accordingly. The proposed algorithm does not assume task periodicity, and requires only previous execution time among a priori information on the task set to schedule. Simulation results show that TLDVS achieves up to 25% energy savings compared with OLDVS, and up to 42% over the non-DVS scheduling.

Temporal locality in IP destination address sequences can be captured by the addresses' reuse distance distribution. Based on measurements from data for a wide range of networks, we propose an accurate empirical model in contrast to results derived from the stationarity assumption of address generation processes.

This work presents a scalable and high performance prediction protocol for optical networks. In the proposed protocol, we develop a mathematical model to maintain the stability of a network system by prediction based on the traffic temporal locality property. All the critical factors, including transceiver tuning time, propagation delay, and processing time for dealing with control packets, are considered in the proposed prediction protocol. Furthermore, our protocol can resolve the bottlenecks attributed to control signaling and electronics processing. The performance evaluation reveals that the proposed scheme can yield the higher bandwidth efficiency and incur a lower packet delay than those of the TDM and conventional reservation schemes. Also, the proposed protocol can flexibly support any scaled network system such as MANs or LANs.