Divya Saxena

Radient: Scalable, memory efficient name lookup algorithm for named data networking

Named Data Networking (NDN) aims to discard the existing host-centric networking paradigm just to replace it with a more practical Content-Centric Networking (CCN) paradigm. CCN allows users to fetch and distribute contents directly using their names. NDN router stores all incoming content requests (׳/׳-delimited string components) in the Pending Interest Table (PIT) until they are satisfied. Multiple requests for the same content are merged in a single PIT entry and when the requested content is available, it is forwarded simultaneously to all the requesters. Although NDN has several benefits over the existing IP-based network, replacing IP addresses with names increases memory consumption and lookup cost. One possible way to restrict memory usage is to use name encoding, i.e., to encode identical components of a name with a unique integer. In this paper, we proposed a novel memory efficient name encoding scheme (called, Radient) for PIT and evaluated it extensively. Our results show that the Radient scheme can reduce memory consumption by 35.45% compared to the ENPT for 29 million names.

SmartHealth-NDNoT : Named Data Network of Things for Healthcare Services

In recent years, healthcare sector has emerged as a major application area of Internet-of-Things (IoT). IoT aims to automate healthcare services through remote monitoring of patients using several vital sign sensors. Remotely collected patient records are then conveyed to the hospital servers through the users smartphones. Healthcare IoT can thus reduce a lot of overhead while allowing people to access healthcare services all the time and everywhere. However, healthcare IoT exchanges data over the IP-centric Internet which has vulnerabilities related to security, privacy, and mobility. Those features are added to the Internet as external add-ons. In order to solve this problem, in this paper, we propose to use Named Data Networking (NDN), which is a future Internet paradigm based on Content-Centric Networking (CCN). NDN has in-built support for user mobility which is well-suited for mobile patients and caregivers. NDN also ensures data security instead of channel security earlier provided by the Internet. In this paper, we have developed NDNoT, which is an IoT solution for smart mobile healthcare using NDN. Our proof-of-concept prototype shows the usability of our proposed architecture.

Implementation and Performance Evaluation of Name-based Forwarding Schemes in V-NDN

Vehicular networking has recently gained great attention. Although TCP/IP protocol has shown great resilience over the years, still it is quite challenging in highly vehicular environments. Recently, researchers proposed the use of a content-centric approach, Named Data Networking (NDN), for enhancing the efficiency of vehicular ad-hoc networks. NDN uses application generated variable-length, location-independent names to retrieve and/or disseminate the content efficiently. Naming allows NDN applications to access multiple network interfaces at the same time without the need of acquiring IP address repeatedly. In this paper, we implement IP-based data forwarding schemes, such as Epidemic, Spray & Wait, and Adaptive Forwarding using NDN on the sparsely-connected real vehicular testbed. We also evaluate these NDN-based forwarding schemes to study the performance of name based forwarding for retrieving and disseminating data. Our experimental results obtained through real vehicular testbed validate the performance and usability of NDN over VANET.

N-FIB: Scalable, memory efficient name-based forwarding

Abstract Named Data Networking (NDN) is a promising future Internet which retrieves the content using their names. Content names composed of strings separated by ‘/’ are stored in the NDN Forwarding Information Base (FIB) to forward the incoming packets further. Though NDN has several benefits over traditional IP-based Internet, storing names instead of IP addresses has two major bottlenecks. While it consumes significantly large memory, it incurs higher search and update time. Another issue is the fast growth of routing table size through which FIB will not fit in existing routers’ line-card memory. Moreover, frequent updates to the FIB can degrade the packet delivery performance. In this paper, we propose a scalable and memory efficient Patricia trie based name forwarding scheme (called, N-FIB) for FIB. N-FIB supports FIB aggregation to significantly minimize the impact of large FIB size and high FIB update cost. Extensive experiment results show that the N-FIB scheme can reduce memory consumption by 68.18% compared to the BP scheme for 29 million named dataset. Moreover, N-FIB is reducing routers’ computation and memory overhead, while supporting strong forwarding correctness.

SmartITS: Smartphone-based identification and tracking using seamless indoor-outdoor localization

Abstract Localization in both indoor and outdoor environments is a long-studied problem. Using Smartphone for localization has also gained popularity recently. However, none of the existing solutions consider seamless localization and tracking of individuals in both indoor and outdoor stretches with significant accuracy. In this paper, we propose a human identification, monitoring, and location tracking system, called SmartITS , which continuously tracks MAC ids of user equipment (Smartphones, BLE tags, and Bluetooth devices) and can provide a Google map-based visualization of their trajectories. Our tracker is a portable mobile entity comprising of a Smartphone and an external Wi-Fi adapter which does not require any extra hardware infrastructure to deploy as well as does not need any modification in hardware design at all. Extensive testing with a prototype testbed system in densely populated areas shows that the SmartITS system can seamlessly track user trajectories in indoor and outdoor stretches with a high aggregate location accuracy which is up to 44.49% more accurate than the simple GPS based location tracking system. Our proof-of-concept prototype shows the usability of SmartITS architecture. We also perform several experiments for evaluating the Smartphone’s performance as a scanner and as a sensor tag.

Design and Verification of an NDN-Based Safety-Critical Application: A Case Study With Smart Healthcare

Internet of Things (IoT) is an emerging networking paradigm where smart devices generate, aggregate, and seamlessly exchange data over the predominantly wireless medium. The Internet, so far, has played a significant role in connecting the world, but still, IoT-based solutions are suffering from two primary challenges: 1) how to secure the sensors data and 2) how to provide efficient local and global communication among various heterogeneous devices. Recently, named data networking (NDN), a future Internet paradigm is proposed to improve and simplify such IoT communication issues. NDN allowed users to fetch data by names irrespective of the actual hosting entity connected through a host-specific IP address. NDN well suits the content-centric pattern of machine-to-machine (M2M) communications predominantly used in IoT. In this paper, we leverage the basic feats of NDN architecture for designing and verification of an NDN-based smart health IoT (NHealthIoT) system. NHealthIoT uses pure-NDN-based M2M communication for capturing and transmission of raw sensor data to the home server which can detect emergency healthcare events using Hidden Markov Model. Emergency events are notified to the cloud server using a novel context-aware adaptive forwarding (Cdf) strategy. Post emergency notifications, and user health information is periodically pulled by the cloud server and by other interested parties using NDN-based publish/subscribe paradigm. The cloud server carries out long-term decision making using probabilistic modeling for detecting the possibility of chronic diseases at the early stage. We extend the workflows intuitive formal approach model for verifying the correctness of NHealthIoT during the emergency. We evaluate the cdf strategy using ndnSIM. Moreover, to validate and to show the usability of NHealthIoT, we develop a proof-of-concept prototype testbed and evaluate it extensively. We also identify some research challenges of the NDN-IoT for researchers.

An NDNoT based Efficient Object Searching Scheme for Smart Home using RFIDs

Internet of Things (IoT) is driven by innumerable sensing devices, RFID tags and other miniature computing entities, which continuously sense, generate and compute data. One can see that our future environment will contain lots of devices that will generate the massive amount of automated data. The presence of resource constrained devices, frequent exchange of data and heterogeneous types of network traffic distinguish IoT from the current Internet. Recently, Named Data Networking (NDN) is proposed as a content retrieval solution which directly deals with application generated variable-length, location-independent names to search and pull contents for a requesting user, irrespective of hosting entity. The use of content names for communication support name-based routing, in-network caching, and security which make the NDN more suitable for IoT. In this paper, we propose a NDN-based searching mechanism (named, Search-NDNoT), which can be used to find any smart item augmented with the RFID in real-world in real-time. An energy-efficient data aggregation algorithm is also proposed to maintain up-to-date data on the server. Our proof-of-concept prototype shows the usability of our proposed system.

Shahbag movement: The tweeted perspective

In recent years, revolutions across the middle-east, mass protests in USA and Spain, and aggregated general discontents in many other countries of the world have lived a cyber life parallel to the streets - mainly in Twitter. Much have been said and believed about Twitter based revolutions. However, there is real dearth of in-depth empirical studies to support those claims. Before the heat of earlier revolutions on Twitter cooled down, a new revolution emerged in the Shahbag Square in Dhaka, capital of Bangladesh. It started by declaration in social networks, quickly gathered huge momentum, and soon got spread all over the country. In this study, we analyzed about a million tweets to study the nature of the movement, the participants and their activities. The results show that the modern revolutions bring together people from all strata of the society around the epicenter and grow in a completely apolitical manner.