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In recent years, Named Data Networking (NDN) has been one of the future internet network architectures by proposing it as a substitute for existing IP networks. NDN assigns addresses/names to data or content, whereas IP assigns addresses to devices. NDN router has a Content Store (CS) component to store requested packets and reducing the time for duplicate content requests. As network architecture, NDN uses several algorithms and strategies in the process. This paper will specifically discuss the forwarding and routing algorithm. Forwarding mechanisms play a significant role in packet delivery on the NDN system. Even though routing was not the main component of the NDN system, the routing mechanism and Routing Information Base remain important, considering Forwarding Information Base was generated after Routing Information Base was generated. Routing has significant control, whereas forwarding can give finer control over the delivery path. Considering the previous statement, the combination of routing and forwarding strategy must be considered to optimize the performance of the packet delivery system on NDN. In addition to getting information about the entire network, centralized routing, and adaptive networking are needed to distribute all network traffic fairly. The challenges and opportunities can also be a reference and a guideline for future Adaptive NDN research.

Target tracking technologies in wireless sensor network (WSNs) environments fall into two categories: active and passive schemes. Unlike with the active positioning schemes, in which the targets are required to hold cooperative devices, the research on passive tracking, i.e., tracking device-free targets, has recently showed promise. In the WSN, device-free targets can be tracked by sensing radio frequency tomography (RFT) on the line-of-sight links (LOSLs). In this paper, we propose a passive tracking scheme exploiting both adaptive-networking LOSL webs and geometric constraint methodology for tracking single targets, as well as multiple targets. Regarding fundamental knowledge, we firstly explore the spatial diversity technique for RFT detection in realistic situations. Then, we analyze the power consumption of the WSN and propose an adaptive networking scheme for the purpose of energy conservation. Instead of maintaining a fixed LOSL density, the proposed scheme can adaptively adjust the networking level to save energy while guaranteeing tracking accuracy. The effectiveness of the proposed scheme is evaluated with computer simulations. According to the results, it is observed that the proposed scheme can sufficiently reduce power consumption, while providing qualified tracking performance.

The increase of a network connectivity may improve network performance, but at the same time, it may also increase the chance of extremely large risk contagion. If external shocks or excess loads at some agents are propagated to the other connected agents due to failure, the domino effects often come with disastrous consequences. How to prevent cascading failures due to external shocks is an important emerging issue. In this paper, we propose mechanisms of mitigating flow-based cascading failure. Our aim is to improve the network's resilience actively and topologically. In the scenario of how to increase cascade resilience actively, we provide a simple micro-foundation based on coordinated incentives to absorb external shocks in order to survive collectively. We propose two types of risk sharing protocols: The topology-based and non-topology-based risk sharing in which network topology plays an important role. These rules employ local sharing algorithms to achieve global shock balancing. The models of shock transfer are designed to investigate some stylized facts on how external or innate shocks tend to be allocated in a network, and how this allocation changes agents' failure probability. In the scenario of how to increase cascade resilience topologically, we provide a rewiring method in which a network is self-organizable to reduce the damage of cascading failure. Simulation results indicate that risk management and adaptive network may dramatically reduce the average size of large cascading failures. [ABSTRACT FROM AUTHOR]

Target tracking technologies in wireless sensor network (WSNs) environments fall into two categories: active and passive schemes. Unlike with the active positioning schemes, in which the targets are required to hold cooperative devices, the research on passive tracking, i.e., tracking device-free targets, has recently showed promise. In the WSN, device-free targets can be tracked by sensing radio frequency tomography (RFT) on the line-of-sight links (LOSLs). In this paper, we propose a passive tracking scheme exploiting both adaptive-networking LOSL webs and geometric constraint methodology for tracking single targets, as well as multiple targets. Regarding fundamental knowledge, we firstly explore the spatial diversity technique for RFT detection in realistic situations. Then, we analyze the power consumption of the WSN and propose an adaptive networking scheme for the purpose of energy conservation. Instead of maintaining a fixed LOSL density, the proposed scheme can adaptively adjust the networking level to save energy while guaranteeing tracking accuracy. The effectiveness of the proposed scheme is evaluated with computer simulations. According to the results, it is observed that the proposed scheme can sufficiently reduce power consumption, while providing qualified tracking performance. [ABSTRACT FROM AUTHOR]