Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userNDN, CoAP, and MQTT: A Comparative Measurement Study in the IoT
355
0
0.0
(
0
)
Added by
Cenk G\\\"undo\\u{g}an
Publication date
2018
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
This paper takes a comprehensive view on the protocol stacks that are under debate for a future Internet of Things (IoT). It addresses the holistic question of which solution is beneficial for common IoT use cases. We deploy NDN and the two popular IP-based application protocols, CoAP and MQTT, in its different variants on a large-scale IoT testbed in single- and multi-hop scenarios. We analyze the use cases of scheduled periodic and unscheduled traffic under varying loads. Our findings indicate that (a) NDN admits the most resource-friendly deployment on nodes, and (b) shows superior robustness and resilience in multi-hop scenarios, while (c) the IP protocols operate at less overhead and higher speed in single-hop deployments. Most strikingly we find that NDN-based protocols are in significantly better flow balance than the UDP-based IP protocols and require less corrective actions.
rate research
Read More
The emerging Internet of Things (IoT) challenges the end-to-end transport of the Internet by low power lossy links and gateways that perform protocol translations. Protocols such as CoAP or MQTT-SN are degraded by the overhead of DTLS sessions, which in common deployment protect content transfer only up to the gateway. To preserve content security end-to-end via gateways and proxies, the IETF recently developed Object Security for Constrained RESTful Environments (OSCORE), which extends CoAP with content object security features commonly known from Information Centric Networks (ICN). This paper presents a comparative analysis of protocol stacks that protect request-response transactions. We measure protocol performances of CoAP over DTLS, OSCORE, and the information-centric Named Data Networking (NDN) protocol on a large-scale IoT testbed in single- and multi-hop scenarios. Our findings indicate that (a) OSCORE improves on CoAP over DTLS in error-prone wireless regimes due to omitting the overhead of maintaining security sessions at endpoints, and (b) NDN attains superior robustness and reliability due to its intrinsic network caches and hop-wise retransmissions.
Under the advocacy of the international community, more and more research topics have been built around the ocean. This paper proposed an implementation scheme of marine wireless sensor network monitoring system based on LoRa and MQTT. Different from the traditional network architecture, the system was constructed by combining with two network forms, and according to their respective characteristics, the overall design followed the transition from LoRa to MQTT. We first used LoRa to interconnect the sensor nodes with the gateway, and on this basis, the collected data was sent to the server visualization platform through MQTT, the backend management server would continuously refresh the monitoring page. At the same time, the client could use a browser-based web application to directly access and call data for global maritime information monitoring. In the future, we will further improve the system and optimize the algorithm, to achieve more dimensions and deeper exploration of the underwater world.
Volunteer computing uses Internet-connected devices (laptops, PCs, smart devices, etc.), in which their owners volunteer them as storage and computing power resources, has become an essential mechanism for resource management in numerous applications. The growth of the volume and variety of data traffic in the Internet leads to concerns on the robustness of cyberphysical systems especially for critical infrastructures. Therefore, the implementation of an efficient Intrusion Detection System for gathering such sensory data has gained vital importance. In this paper, we present a comparative study of Artificial Intelligence (AI)-driven intrusion detection systems for wirelessly connected sensors that track crucial applications. Specifically, we present an in-depth analysis of the use of machine learning, deep learning and reinforcement learning solutions to recognize intrusive behavior in the collected traffic. We evaluate the proposed mechanisms by using KD99 as real attack data-set in our simulations. Results present the performance metrics for three different IDSs namely the Adaptively Supervised and Clustered Hybrid IDS (ASCH-IDS), Restricted Boltzmann Machine-based Clustered IDS (RBC-IDS) and Q-learning based IDS (QL-IDS) to detect malicious behaviors. We also present the performance of different reinforcement learning techniques such as State-Action-Reward-State-Action Learning (SARSA) and the Temporal Difference learning (TD). Through simulations, we show that QL-IDS performs with 100% detection rate while SARSA-IDS and TD-IDS perform at the order of 99.5%.
Routing in NDN networks must scale in terms of forwarding table size and routing protocol overhead. Hyperbolic routing (HR) presents a potential solution to address the routing scalability problem, because it does not use traditional forwarding tables or exchange routing updates upon changes in network topologies. Although HR has the drawbacks of producing sub-optimal routes or local minima for some destinations, these issues can be mitigated by NDNs intelligent data forwarding plane. However, HRs viability still depends on both the quality of the routes HR provides and the overhead incurred at the forwarding plane due to HRs sub-optimal behavior. We designed a new forwarding strategy called Adaptive Smoothed RTT-based Forwarding (ASF) to mitigate HRs sub-optimal path selection. This paper describes our experimental investigation into the packet delivery delay and overhead under HR as compared with Named-Data Link State Routing (NLSR), which calculates shortest paths. We run emulation experiments using various topologies with different failure scenarios, probing intervals, and maximum number of next hops for a name prefix. Our results show that HRs delay stretch has a median close to 1 and a 95th-percentile around or below 2, which does not grow with the network size. HRs message overhead in dynamic topologies is nearly independent of the network size, while NLSRs overhead grows polynomially at least. These results suggest that HR offers a more scalable routing solution with little impact on the optimality of routing paths.
Quality of Service (QoS) in the IP world mainly manages forwarding resources, i.e., link capacities and buffer spaces. In addition, Information Centric Networking (ICN) offers resource dimensions such as in-network caches and forwarding state. In constrained wireless networks, these resources are scarce with a potentially high impact due to lossy radio transmission. In this paper, we explore the two basic service qualities (i) prompt and (ii) reliable traffic forwarding for the case of NDN. The resources we take into account are forwarding and queuing priorities, as well as the utilization of caches and of forwarding state space. We treat QoS resources not only in isolation, but correlate their use on local nodes and between network members. Network-wide coordination is based on simple, predefined QoS code points. Our findings indicate that coordinated QoS management in ICN is more than the sum of its parts and exceeds the impact QoS can have in the IP world.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
