Internet Nodes Research Articles

A Routing Algorithm to Optimize the Energy Efficacy of Nodes in Internet of Things

A Routing Algorithm to Optimize the Energy Efficacy of Nodes in Internet of Things

Optimization of cluster resource indexing of Internet of Things based on improved ant colony algorithm

In Internet of Things, the resource distribution is random in space, which leads to the poor precision ratio of the cluster resource indexing of Internet of Things, so in order to improve the information fusion and dispatching ability of Internet of Things, it is necessary to optimize the resource indexing of Internet of Things. Therefore, an algorithm for cluster resource indexing of Internet of Things based on improved ant colony algorithm is proposed in this paper. Directed graph models are used to construct a distribution structure model of cluster resource indexing nodes of Internet of Things, carry out semantic association feature extraction in the cluster resource storage information flow of Internet of Things. And the improved ant colony algorithm is used to crawl and capture cluster information in Internet of Things. According to the ant colony trajectory information, the velocity and position of the cluster resource indexing of Internet of Things are updated, and the balanced ant colony algorithm is used to carry out the global search and local search to resources and initialize the clustering center, and the target function of the cluster resource indexing of Internet of Things is constructed and the optimization parameter is solved with the constraint condition of the minimum variance of the whole fitness. The strong ability of global optimization of the ant colony algorithm is used to realize resource indexing optimization. Simulation results show that the improved algorithm can quickly realize resource index convergence, effectively escape local minimum points, and has strong global search ability and relatively high resource indexing precision ratio.

A trusted attestation mechanism for the sensing nodes of Internet of Things based on dynamic trusted measurement

Internet of things has been widely applied to industrial control, smart city and environmental protection, in these application scenarios, sensing node needs to make real-time response to the feedback control of the application layer. Therefore, it is necessary to monitor whether or not awareness nodes are trusted in real time, but the existing mechanisms for trusted certification lack the real-time measurement and tracking of the sensing node. To solve the above problems, this paper proposes a dynamic metric based authentication mechanism for sensing nodes of Internet of things. Firstly, the dynamic trustworthiness measure of the sensing nodes is carried out by introducing the computational function such as the trust function, the trustworthiness risk assessment function, the feedback control function and the active function of the sensing node. The dynamic trustworthiness measure of sensing nodes from multiple dimensions can effectively describe the change of trusted value of sensing nodes. Then, on the basis of this, a trusted attestation based on node trusted measure is realized by using the revocable group signature mechanism of local verifier. The mechanism has anonymity, unforgeability and traceability, which is proved the security in the standard model. Simulation experiments show that the proposed trusted attestation mechanism is flexible, practical and efficient and has better attack resistance. It can effectively guarantee the reliable data transmission of nodes and realize the dynamic tracking of node reliability, which has a lower impact on system performance.

Internet Node as a Network of Relationships: Sociotechnical Aspects of an Internet Exchange Point

Internet Node as a Network of Relationships: Sociotechnical Aspects of an Internet Exchange Point

Efficient Maintenance of AODV Routes in the Vehicular Communication Environment with Sparsely Placed Road Side Units

Thanks to the vehicular communication network, vehicles on the road can communicate with other vehicles or nodes in the global Internet. In this study, we propose an enhanced routing mechanism based on AODV so that road side units (RSUs) can provide continuous services such as video streaming services to vehicles which may be intermittently located outside of the coverage areas of RSUs. In the highway environment with sparsely placed RSUs, the communications between RSUs and vehicles are frequently disconnected due to high vehicular speeds. To resolve this problem, both V2I and V2V communications are utilized. In order to reduce the route recovery time and the number of route failures in the sparsely placed RSU environment, backup routes are established through the vehicles with longer direct communication duration with the RSU. The backup route substitutes the main route upon route disconnection. Also, for the efficient handover to the next RSU, the route shortening mechanism is proposed. For the performance evaluation of the proposed mechanism, we carried out the NS-3-based simulations.

Macroscopic Geographical Speed of Data Transmission in European Internet

The paper deals with geographical speed of IP data transmission in the European Internet. We measure the speed using a set of PlanetLab servers with known physical location. Based on the results we identify typical maximum geographical distance that data can travel for given communication latency, provided that the linear latency-to-distance transformation is preferred. An estimation of the typical maximum distance between two Internet nodes may help to improve certain geolocation problems. We show that the typical maximum distance results in a smaller delimited area of possible node locations, still including the correct location.DOI: http://dx.doi.org/10.5755/j01.itc.46.4.16113

Location Accuracy of Commercial IP Address Geolocation Databases

This paper deals with finding the geographical location of Internet nodes remotely with no need to communicate with the nodes located (client-independently). IP geolocation is used in a number of areas, such as content personalisation, on-line fraud prevention and detection, and digital media law enforcement. One of the main concerns when studying the accuracy of client-independent geolocation is the groundtruth dataset. As we show in the related work, the used groundtruth influences the results a lot. We construct an error-free groundtruth dataset consisting of nodes with GPS-precise locations. We also record the country, region, city, and ISP for each groundtruth node. Using the created groundtruth, we study the accuracy of eight IP location databases in a number of scenarios, such as effect of city area and population, effect of ISP assignment, and number of not-returned locations.DOI: http://dx.doi.org/10.5755/j01.itc.46.3.14451

A High Efficient Self-Organizing Network Protocol for Large Scale Aware Nodes in Internet of Things

There are a lot of researches on self-organizing network at present. However, due to the characteristics of topological change of the Internet of Things, node resource constraints and random distribution and so on. Most of the existing self-organizing network are not applicable. This paper is aimed at the characteristics of the Internet of Things, and draws lessons from small world model, energy multi-path routing and hybrid routing algorithm. On the basis of GEAR protocol, a model of high efficient self-organizing network for large scale aware node is proposed: A multi-path hybrid routing model based on small world model, referred as SMH (Small World Multi-Path Hybrid Routing) model. In this paper, the model is implemented and an improved protocol based on GEAR is obtained, which is SMH-GEAR protocol. And SMH-GEAR protocol and GEAR protocol are compared and analyzed with simulation by using NS-2 network simulation platform. The result of the experiment shows SMH-GEAR protocol is better than GEAR protocol in terms of overall performance.

Trust attestation mechanism for the sensing layer nodes of Internet of Things

The main function of Internet of Things is to collect and transmit data. At present, the data transmission in Internet of Things lacks effective trust attestation mechanism and trust traceability mechanism of data source. To solve the above problems, a trust attestation mechanism for sensing layer nodes is presented. First a trusted group is established, and the node which is going to join the group needs to attest its identity and key attributes to the higher level node. Then the dynamic trust measurement value of the node can be obtained by measuring the node data transmission behavior. Finally the node encapsulates the key attributes and trust measurement value to use short message group signature to attest its trust to the challenger. This mechanism can measure the data sending and receiving behaviors of sensing nodes and track the data source, and it does not expose the privacy information of nodes and the sensing nodes can be traced effectively. The trust measurement for sensing nodes and verification is applicable to Internet of Things and the simulation experiment shows the trust attestation mechanism is flexible, practical and efficient. Besides, it can accurately and quickly identify the malicious nodes at the same time. The impact on the system performance is negligible.

Cooperation and end‐to‐end in the Internet

SummaryThis paper analyzes the motivation and strategies for ensuring cooperative behavior among hosts and customer networks in the Internet and 5G networks. The hypothesis is that better cooperation among the benevolent entities could improve the overall Internet welfare, motivating the need for adoption of cooperative security. However, in state of the art, the prevalent security approach in the Internet is based on self‐help, while the adoption of cooperative methods is progressing slowly. At the same time, the ubiquitous reliance on 5G and mission critical nature of some of the new services, for example, ultrareliable (machine‐to‐machine) communication and Internet of things, requires that 5G will do its best to curb the malicious (noncooperative) behavior from becoming a cause of failure to the legitimate services. In this paper, we relate our analysis of the conditions for sustainable cooperation in the Internet with the famous end‐to‐end principle, and present the hypothesis that there is no end‐to‐end solution to the problem of ensuring cooperation among Internet hosts. Game theory allows studying the outcomes of interactions among the players with conflicting interests. We use it to study the hypothesis and show that introducing the reputation of Internet nodes and customer networks can lead to cooperation, which improves the overall Internet welfare and reduces the payoffs of malicious actors. We study the possible response of noncooperative users with advanced defection strategies and the resulting outcomes. We argue that 5G shall make significant progress towards uprooting the selfish behavior and malicious activities using cooperation and relate it with motivation for providing ubiquitous connectivity and ultrareliable services. The paper concludes by summarizing our earlier work on the application of the proposed methods of cooperation to 5G and the Internet; outlining how cooperation in security is not only desirable but also feasible.

An architecture for aggregating information from distributed data nodes for industrial internet of things

The current Internet of Things (IoT) has made it very convenient to obtain information about a product from a single data node. However, in many industrial applications, information about a single product can be distributed in multiple different data nodes, and aggregating the information from these nodes has become a common task. In this paper, we provide a distributed service-oriented architecture for this task. In this architecture, each manufacturer provides service for their own products, and data nodes keep the information collected by themselves. Semantic technologies are adopted to handle problems of heterogeneity and serve as the foundation to support different applications. Finally, as an example, we illustrate the use of this architecture to solve the problem of product tracing.

Analysis and performance assessment of a fragment retransmission scheme for energy efficient IEEE 802.11 WLANs.

Backoff-free fragment retransmission (BFFR) scheme enhances the performance of legacy MAC layer fragmentation by eliminating contention overhead. The eliminated overhead is the result of backoff executed before a retransmission attempt is made when fragment transmission failure occurs within a fragment burst. This paper provides a mathematical analysis of BFFR energy efficiency and further assesses, by means of simulations, the energy efficiency, throughput and delay obtained when BFFR is used. The validity of the new scheme is evaluated in different scenarios namely, constant bit rate traffic, realistic bursty internet traffic, node mobility, rigid and elastic flows and their combinations at different traffic loads. We also evaluate and discuss the impact of BFFR on MAC fairness when the number of nodes is varied from 4 to 10. It is shown that BFFR has advantages over legacy MAC fragmentation scheme in all the scenarios.

A Highly Efficient Reconfigurable Charge Pump Energy Harvester With Wide Harvesting Range and Two-Dimensional MPPT for Internet of Things

A monolithic microwatt-level charge pump energy harvester is proposed for smart nodes of Internet of Things (IOT) networks. Due to the variation of the available voltage and power in IOT scenarios, the charge pump was optimized by the proposed architecture and circuit level innovations. First, a reconfigurable charge pump is introduced to provide the hybrid conversion ratios (CRs) as $1\frac {1}{3} \times$ up to $8 \times$ for minimizing the charge redistribution loss. Second, the reconfigurable feature also dynamically tunes to maximum power point tracking (MPPT) with the frequency modulation, resulting in a two-dimensional (2-D) MPPT. Therefore, the voltage conversion efficiency (VCE) and the power conversion efficiency (PCE) are enhanced and flattened. Third, the constant-on-time (COT) scheme from the regulation part was reused with the proposed MPPT arbiter as a sensing approach, which eliminates the conventional power hungry current sensor. The proposed energy harvester is capable of harvesting various energy sources, such as a photovoltaic (PV) cell and a thermoelectric generator (TEG), with a wide input range from 0.45 to 3 V and a regulated 3.3 V output voltage for the IOT smart nodes. Measured results showed that the harvester achieved a flattened and improved PCE as high as 89% for ultra-low power operation capability below $50\,\upmu{\text {W}}$ .

Detecting TCP Based Attacks Using Data Mining Algorithms

Intrusion Detection Systems have become a necessary in computer networking security of largest networks. In the recent years, the system needs to identify new intrusion in largest datasets in a timely manner because internet to instantly access information at anytime from anywhere. That is a massive increasing of data traffic and internet nodes. Therefore, to refine an IDS’s performance and computing time is a one of the important challenges in computer network security field. We are introducing by this paper studying the effects of TCP based attacks on AI algorithms computing time and detection ratio using KDDCUP dataset and our collected dataset. We are to gather network traffic; normal and abnormal containing attack are collected by SNORT. We extract features in TCP headers of the packets in the collected dataset such as sequence and acknowledge numbers, window size, control flags, and an event which is time between neighbour segments. First we normalize the feature set to reduce dimensionality of our input feature space and apply Pearson correlation to measure the dependability of the relationship. Finally, the selected subset of the features is given to learn the classifiers: J-48, Naive Bayes and ANNs. By adopting the concepts of machine learning and datamining, we could detect 98% of abnormal traffic containing attacks.

IGOD: identification of geolocation of cloud datacenters

The geolocation of data has become a key concern with the evolution of cloud computing. Although data migration is quite common and sometimes essential for the purpose of load balancing or service guarantees, at times, it creates a risk for the user and could even violate the service agreement. A malicious service provider could also relocate the data, which could jeopardize data privacy and security. In this paper, we introduce a novel algorithm called IGOD to geolocate a cloud data center which can also be used for geolocating internet nodes. IGOD efficiently geolocates any target data center with higher accuracy and less cost. It provides audit control and assurance against such cloud storage providers who may move around a customer's data. We analyze and compare IGOD with currently available solutions of geolocating a target. We have used PlanetLab to validate IGOD and establish its cost-effective feature. To do so, we first use our own data collection to geolocate the test data center using emulation and compare IGOD's performance with other schemes. Finally, we use it to geolocate one of the Amazon S3 data centers. Our comparison shows that IGOD provides relatively higher location accuracy and is cost-effective (uses less resources).

MAVIN: A MAC address coding based virtual network platform

Network virtualization is a promising way for network innovation. Efforts have been made to develop virtual network platforms for both network researches and business applications. In this paper, we aim to provide a new solution to address the shortcomings of existing solutions. We propose MAVIN - a MAC address coding based virtual network platform. MAVIN avoids changing the nodes of the current Internet, and can provide high performance virtual networks with user-specified network protocols and link performance parameters. Comparing to existing network virtualization schemes, MAVIN can achieve layer-2 virtualization which has no extra forwarding overhead. We implement the virtual router prototype of MAVIN and establish a real MAVIN platform to evaluate its performance. Evaluation results show that MAVIN can support high performance virtual networks with excellent scalability.

Globally Stable Wireless Data Flow Control

Packet data flow control from internet nodes to wireless transmission nodes will become increasingly important in 5G wireless systems. One reason is the new requirement to maintain and guarantee a maximum round-trip loop delay for high-bandwidth feedback control applications. Another driver is the emerging multipoint mobile broadband internet access, where data starvation needs to be avoided in the transmit queue buffers of the wireless transmission nodes. Moreover, robust global stability is a requirement, since an only locally stable data flow controller would have a nonzero likelihood to malfunction algorithmically. The resulting networked control problem is further complicated by an uncertain internet backhaul loop delay, in combination with a one-directional data flow that introduces saturation in the feedback loop. The paper therefore contributes with a proof of global robust stability for a nonlinear networked window-based packet flow control algorithm. The performance and stability of the controller are assessed with simulation, which shows that the algorithm performs as required.

A Highly Efficient Ultralow Photovoltaic Power Harvesting System With MPPT for Internet of Things Smart Nodes

Implementing a monolithic highly efficient ultralow photovoltaic (PV) power harvesting system is pivotal for smart nodes of Internet of things (IOT) networks. This paper proposes a fully integrated harvesting system in 0.18-μm CMOS technology. Utilizing a small commercial solar cell of 2.5 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , the proposed system can provide 0-29 μW of power, which is much higher than the commonly used passive radio-frequency identification devices in IOT application. The hill-climbing maximum power point tracking algorithm is developed in an energy-efficient manner to tune the input impedance of the system and guarantee adaptive maximum power transfer under wide illumination conditions. The detailed impedance tuning approach is implemented with a capacitor value modulation to eliminate the quiescent power consumption as well as to achieve a higher efficiency than the traditional pulse-frequency modulation scheme. A supercapacitor is utilized for buffering, energy storing, and filtering purposes, which enables more functions of the IOT smart nodes such as active sensing and system-on-chip (SOC) signal processing. The output voltage ranges between 3.0 and 3.5 V for different device loads, such as sensors, SOC, or wireless transceivers. The measured results confirm that this PV harvesting system achieves both ultralow operation capability under 20 μW and a selfsustaining efficiency of 89%.

Estimation of Internet Node Location by Latency Measurements - The Underestimation Problem

In this paper we deal with discovering a geographic location of a node in the Internet. Knowledge of location is a fundamental element for many location based applications and web services. We focus on location finding without any assistance of the node being located - client-independent estimation. We estimate a location using communication latency measurements between nodes in the Internet. The latency measured is converted into a geographic distance which is used to derive a location by the multilateration (triangulation) principle. We analyse the latency-to-distance conversion with a consideration of location underestimation which is a product of multilateration failure. We demonstrate that location underestimations do not appear in experimental conditions. However with a real-world scenario, a number of devices cannot be located due to underestimations. Finally, we propose a modification to reduce the number of underestimations in real-world scenarios.DOI: http://dx.doi.org/10.5755/j01.itc.44.3.8353

A new online anomaly learning and detection for large-scale service of Internet of Thing

The online anomaly detection has been propounded as the key idea of monitoring fault of large-scale sensor nodes in Internet of Things. Now, the exciting progresses of research have been made in online anomaly detection area. However, the highly dynamic distributing character of Internet of Things makes the anomaly detection scheme difficult to be used in online manner. This paper presents a new online anomaly learning and detection mechanism for large-scale service of Internet of Thing. Firstly, our model uses the reversible-jump MCMC learning to online learn anomaly-free of dynamics network and service data. Next, we perform a structural analysis of IoT-based service topology by network utility maximization theory. The results of experiment demonstrate the method accuracy in forecasting dynamics network and service structures from synthetic data.