缓存是命名数据网络(named data networking,NDN)有别于传统网络最突出的特性之一,NDN中默认所有节点都具有缓存所有经过数据的功能.这种"处处缓存"策略导致网内大量冗余数据的产生,使网内缓存被严重浪费.针对上述问题,首次...缓存是命名数据网络(named data networking,NDN)有别于传统网络最突出的特性之一,NDN中默认所有节点都具有缓存所有经过数据的功能.这种"处处缓存"策略导致网内大量冗余数据的产生,使网内缓存被严重浪费.针对上述问题,首次提出了一种基于节点分类(based on node classification,BNC)的数据存储策略.基于节点位置的不同,将数据返回客户端所经过的节点分为"边缘"类节点与"核心"类节点.当数据经过"核心"类节点时,通过权衡该类节点的位置与数据在不同节点的流行度分布,将数据存储在对其他节点最有利的节点中;当数据经过"边缘"类节点时,通过该数据流行度来选择最有利于客户端的位置.仿真结果表明,提出的策略将有效提高数据命中率,减少数据请求时延和距离.展开更多
Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offer...Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offers opportunities but may also bear risks. A hitherto neglected aspect is the possible increase in power consumption as smart devices in IoT applications are expected to be reachable by other devices at all times. This implies that the device is consuming electrical energy even when it is not in use for its primary function. Many researchers’ communities have started addressing storage ability like cache memory of smart devices using the concept called—Named Data Networking (NDN) to achieve better energy efficient communication model. In NDN, memory or buffer overflow is the common challenge especially when internal memory of node exceeds its limit and data with highest degree of freshness may not be accommodated and entire scenarios behaves like a traditional network. In such case, Data Caching is not performed by intermediate nodes to guarantee highest degree of freshness. On the periodical updates sent from data producers, it is exceedingly demanded that data consumers must get up to date information at cost of lease energy. Consequently, there is challenge in maintaining tradeoff between freshness energy consumption during Publisher-Subscriber interaction. In our work, we proposed the architecture to overcome cache strategy issue by Smart Caching Algorithm for improvement in memory management and data freshness. The smart caching strategy updates the data at precise interval by keeping garbage data into consideration. It is also observed from experiment that data redundancy can be easily obtained by ignoring/dropping data packets for the information which is not of interest by other participating nodes in network, ultimately leading to optimizing tradeoff between freshness and energy required.展开更多
文摘缓存是命名数据网络(named data networking,NDN)有别于传统网络最突出的特性之一,NDN中默认所有节点都具有缓存所有经过数据的功能.这种"处处缓存"策略导致网内大量冗余数据的产生,使网内缓存被严重浪费.针对上述问题,首次提出了一种基于节点分类(based on node classification,BNC)的数据存储策略.基于节点位置的不同,将数据返回客户端所经过的节点分为"边缘"类节点与"核心"类节点.当数据经过"核心"类节点时,通过权衡该类节点的位置与数据在不同节点的流行度分布,将数据存储在对其他节点最有利的节点中;当数据经过"边缘"类节点时,通过该数据流行度来选择最有利于客户端的位置.仿真结果表明,提出的策略将有效提高数据命中率,减少数据请求时延和距离.
文摘Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offers opportunities but may also bear risks. A hitherto neglected aspect is the possible increase in power consumption as smart devices in IoT applications are expected to be reachable by other devices at all times. This implies that the device is consuming electrical energy even when it is not in use for its primary function. Many researchers’ communities have started addressing storage ability like cache memory of smart devices using the concept called—Named Data Networking (NDN) to achieve better energy efficient communication model. In NDN, memory or buffer overflow is the common challenge especially when internal memory of node exceeds its limit and data with highest degree of freshness may not be accommodated and entire scenarios behaves like a traditional network. In such case, Data Caching is not performed by intermediate nodes to guarantee highest degree of freshness. On the periodical updates sent from data producers, it is exceedingly demanded that data consumers must get up to date information at cost of lease energy. Consequently, there is challenge in maintaining tradeoff between freshness energy consumption during Publisher-Subscriber interaction. In our work, we proposed the architecture to overcome cache strategy issue by Smart Caching Algorithm for improvement in memory management and data freshness. The smart caching strategy updates the data at precise interval by keeping garbage data into consideration. It is also observed from experiment that data redundancy can be easily obtained by ignoring/dropping data packets for the information which is not of interest by other participating nodes in network, ultimately leading to optimizing tradeoff between freshness and energy required.
