A Light-Weight Forwarding Plane for Content-Centric Networks

We present CCN-DART, a more efficient forwarding approach for content-centric networking (CCN) than named data networking (NDN) that substitutes Pending Interest Tables (PIT) with Data Answer Routing Tables (DART) and uses a novel approach to eliminate forwarding loops. The forwarding state required at each router using CCN-DART consists of segments of the routes between consumers and content providers that traverse a content router, rather than the Interests that the router forwards towards content providers. Accordingly, the size of a DART is proportional to the number of routes used by Interests traversing a router, rather than the number of Interests traversing a router. We show that CCN-DART avoids forwarding loops by comparing distances to name prefixes reported by neighbors, even when routing loops exist. Results of simulation experiments comparing CCN-DART with NDN using the ndnSIM simulation tool show that CCN-DART incurs 10 to 20 times less storage overhead

Enabling Correct Interest Forwarding and Retransmissions in a Content Centric Network

We show that the mechanisms used in the name data networking (NDN) and the original content centric networking (CCN) architectures may not detect Interest loops, even if the network in which they operate is static and no faults occur. Furthermore, we show that no correct Interest forwarding strategy can be defined that allows Interest aggregation and attempts to detect Interest looping by identifying Interests uniquely. We introduce SIFAH (Strategy for Interest Forwarding and Aggregation with Hop-Counts), the first Interest forwarding strategy shown to be correct under any operational conditions of a content centric network. SIFAH operates by having forwarding information bases (FIBs) store the next hops and number of hops to named content, and by having each Interest state the name of the requested content and the hop count from the router forwarding an Interest to the content. We present the results of simulation experiments using the ndnSIM simulator comparing CCN and NDN with SIFAH. The results of these experiments illustrate the negative impact of undetected Interest looping when Interests are aggregated in CCN and NDN, and the performance advantages of using SIFAH

Efficient multicasting in Content-Centric Networks using locator-based Forwarding state

The Named Data Networking (NDN) and Content- Centric Networking (CCNx) architectures use a forwarding plane that requires large Forwarding Information Bases (FIB) listing the next hops to name prefixes and Pending Interest Tables (PIT) that maintain per-Interest forwarding state. We introduce CCN- RAMP (Routing to Anchors Matching Prefixes), a new approach to content-centric networking that substitutes the large FIBs and PITs used in NDN and CCNx with small forwarding tables listing anonymous sources of Interests and routers that announce name prefixes being local. The results of simulation experiments comparing NDN with CCN-RAMP based on ndnSIM show that CCN-RAMP requires forwarding state that is orders of magnitude smaller than what NDN requires, and attains smaller end-to-end delays in the dissemination of multicast content to consumers

Forwarding and Routing Algorithms for Information Centric and Mobile Ad Hoc Networks

It has been shown that the current Internet architecture is not well suited to current and emerging traffic demands. Many content distribution technologies such as content delivery networks (CDN), and peer-to-peer systems have emerged to allow content access by name rather than server location or address. Furthermore, to respond to the increasing volumes of traffic for such applications as video on demand and cloud computing, many efforts have been undertaken to enable caching, content replication, and processing within the network. Such technologies are highly dependent on the distribution channel and perform as an overlay on the current Internet architecture, which results in a number of inefficiencies.Information Centric Network (ICN) architectures have been proposed as an alternative to the current Internet architecture. The focus of ICN architectures is on caching, replicating, and distributing data by name, independently of their locations. In this dissertation, the most popular ICN architectures, Named Data Networking (NDN) and Content-Centric Networking (CCNx) are evaluated and problems of such designs in different aspects such as caching, forwarding, and security are introduced. To address the weaknesses of these architectures, we propose a new ICN architectures and compare it with NDN and CCNx using simulation experiments. The results of these experiments show that the proposed new architectures improve network performance in terms of loop detection, forwarding table size, routing table size, processing overhead, and scalability.Although the aggregation of packets which is used in some ICN architectures might not be very helpful in presence of in-network caching, we show that it can be highly effective where the amount of signaling overhead plays a major role in the performance of the protocol. We propose a new routing algorithm for mobile ad hoc networks, called ADARA, which improves the performance of on-demand routing protocols by ”aggregating” route request packets. Results indicate that aggregating route requests can make on-demand routing more efficient than existing proactive or on-demand routing protocols

Enabling Correct Interest Forwarding and Retransmissions in a Content Centric Network

We show that the mechanisms used in the name data networking (NDN) and the original content centric networking (CCN) architectures may not detect Interest loops, even if the network in which they operate is static and no faults occur. Furthermore, we show that no correct Interest forwarding strategy can be defined that allows Interest aggregation and attempts todetect Interest looping by identifying Interests uniquely. We introduce SIFAH (Strategy for Interest Forwarding and Aggregation with Hop-Counts), the first Interest forwarding strategy shown to be correct under any operational conditions of a content centric network. SIFAH operates by having forwarding information bases (FIBs) store the next hops and number of hops to named content, and by having each Interest state the name of the requested content and the hop count from the router forwarding an Interest to the content. We present the results of simulation experiments using the ndnSIM simulator comparing CCN and NDN with SIFAH. The results of these experiments illustrate the negative impact of undetected Interest looping when Interests are aggregated in CCN and NDN, and the performance advantages of using SIFAH

From Big to Little Data for Natural Disaster Recovery: How Online and On-the-ground Activities are Connected?

Abstract: Following a major natural disaster, many turn to social media to communicate about their situation and try to seek help in disaster recovery. With millions of social media posts, it can be difficult for disaster management organizations to tap into these immense social networks to find the data needed and to connect individuals to networks that can provide assistance. This study takes big data analytic methods and applies them to a specific context, examining how active and influential members of Facebook groups aided in disaster recovery following Hurricane Sandy. It uses network analysis methods for finding influential members and a web-survey for learning about their background and volunteer activity inside and outside of their Facebook groups. The findings show that the majority of the active online members are also actively involved in on-theground recovery activities. They also have the capacity and willingness to work as volunteers. These members have important roles in the integration of online and on-theground disaster recovery efforts. Local governments and disaster management organizations should be prepared to incorporate social media data in their formal disaster recovery processes. This incorporation requires the integration of big data analysis methods with social science theories and methods

Efficient Multicasting in Content-Centric Networks Using Locator-based Forwarding State

The Named Data Networking (NDN) and Content- Centric Networking (CCNx) architectures use a forwarding plane that requires large Forwarding Information Bases (FIB) listing the next hops to name prefixes and Pending Interest Tables (PIT) that maintain per-Interest forwarding state. We introduce CCN- RAMP (Routing to Anchors Matching Prefixes), a new approach to content-centric networking that substitutes the large FIBs and PITs used in NDN and CCNx with small forwarding tables listing anonymous sources of Interests and routers that announce name prefixes being local. The results of simulation experiments comparing NDN with CCN-RAMP based on ndnSIM show that CCN-RAMP requires forwarding state that is orders of magnitude smaller than what NDN requires, and attains smaller end-to-end delays in the dissemination of multicast content to consumers