142 research outputs found
Threshold signature in off-chain components to manage inter-chain transactions
Blockchain is now a widespread technology. However,
achieving mass adoption for specific applications requires
overcoming several challenges inherent to the use of distributed algorithms and cryptographic primitives, which are central to blockchain technology. One of the main obstacles is interoperability between different blockchains, as each blockchain acts as an isolated environment. To address the interoperability problem, it is essential to use off-chain processes capable of interconnecting the blockchains in question. If the interconnected blockchains are private or consortium-based, attention must be paid to both the confidentiality of the data exchanged and the authority of those authorised to operate on them. We propose a novel approach in which each blockchain implements its own off-chain component. Each off-chain component does not communicate with the others and uses a threshold digital signature scheme as cryptographic proof aimed at improving the control and management of inter-chain transactions, alongside computational complexity reductions
UHEED - an unequal clustering algorithm for wireless sensor networks
Prolonging the lifetime of wireless sensor networks has always been a determining factor when designing and deploying such networks. Clustering is one technique that can be used to extend the lifetime of sensor networks
by grouping sensors together. However, there exists the hot spot problem which causes an unbalanced energy consumption in equally formed clusters. In this paper, we propose UHEED, an unequal clustering algorithm which mitigates this problem and which leads to a more uniform residual energy in the network and improves the network lifetime. Furthermore, from the simulation results presented, we were able to deduce the most appropriate unequal cluster size to be used
DALICA: intelligent agents for user profile deduction.
In this paper we are going to discuss the potential contributions that agent technology can bring into an Ambient Intelligence scenario, related to the fruition of cultural assets. The users are located in an area which is known to the agents: in the application, the users are the visitors of Villa Adriana, an archaeological site in Tivoli, near Rome (Italy). Agents are aware of user moves by means of Galileo satellite signal, i.e., the proposed application is based on a blend of different technologies.
The agents, developed in the DALI logic programming language, pro-actively learn and/or enhance users profiles and are thus capable to competently assist the users during their visit, to elicit habits and preferences and
to propose cultural assets to the users according to the learned profile
Packet arrival analysis in wireless sensor networks
Distributed sensor networks have been discussed for more than 30 years, but the vision of Wireless Sensor Networks (WSNs) has been brought into reality only by the rapid advancements in the areas of sensor design, information technologies, and wireless networks that have paved the way for the proliferation of WSNs. The unique characteristics of sensor networks introduce new challenges, amongst which prolonging the sensor lifetime is the most important. WSNs have seen a tremendous growth in various application areas including health care, environmental monitoring, security, and military purposes despite prominent performance and availability challenges. Clustering plays an important role in enhancement of the life span and scalability of the network, in such applications. Although researchers continue to address these grand challenges, the type of distributions for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. Modelling the behaviour of the networks becomes essential for estimating the performance metrics and further lead to decisions for improving the network performance, hence highlighting the importance of identifying the type of inter-arrival distributions at the cluster head. In this paper, we present extensive discussions on the assumptions of exponential distributions in WSNs, and present numerical results based on Q-Q plots for estimating the arrival distributions. The work is further extended to understand the impact of end-to-end delay and its effect on inter-arrival time distributions, based on the type of medium access control used in WSNs. Future work is also presented on the grounds that such comparisons based on simple eye checks are insufficient. Since in many cases such plots may lead to incorrect conclusions, demanding the necessity for validating the types of distributions. Statistical analysis is necessary to estimate and validate the empirical distributions of the arrivals in WSNs
Does the assumption of exponential arrival distributions in wireless sensor networks hold?
Wireless Sensor Networks have seen a tremendous growth in various application areas despite prominent performance and availability challenges. One of the common configurations to prolong the lifetime and deal with the path loss phenomena having a multi-hop set-up with clusters and cluster heads to relay the information. Although researchers continue to address these challenges, the type of distribution for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. The general practice in published works is to compare an empirical exponential arrival distribution of wireless sensor networks with a theoretical exponential distribution in a Q-Q plot diagram. In this paper, we show that such comparisons based on simple eye checks are not sufficient since, in many cases, incorrect conclusions may be drawn from such plots. After estimating the Maximum Likelihood parameters of empirical distributions, we generate theoretical distributions based on the estimated parameters. By conducting Kolmogorov-Smirnov Test Statistics for each generated inter-arrival time distributions, we find out, if it is possible to represent the traffic into the cluster head by using theoretical distribution. Empirical exponential arrival distribution assumption of wireless sensor networks holds only for a few cases. There are both theoretically known such as Gamma, Log-normal and Mixed Log-Normal of arrival distributions and theoretically unknown such as non-Exponential and Mixed cases of arrival in wireless sensor networks. The work is further extended to understand the effect of delay on inter-arrival time distributions based on the type of medium access control used in wireless sensor networks
Packet Arrival Analysis in Wireless Sensor Networks
Distributed sensor networks have been discussed for more than 30 years, but the vision of Wireless Sensor Networks (WSNs) has been brought into reality only by the rapid advancements in the areas of sensor design, information technologies, and wireless networks that have paved the way for the proliferation of WSNs. The unique characteristics of sensor networks introduce new challenges, amongst which prolonging the sensor lifetime is the most important. WSNs have seen a tremendous growth in various application areas including health care, environmental monitoring, security, and military purposes despite prominent performance and availability challenges. Clustering plays an important role in enhancement of the life span and scalability of the network, in such applications. Although researchers continue to address these grand challenges, the type of distributions for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. Modelling the behaviour of the networks becomes essential for estimating the performance metrics and further lead to decisions for improving the network performance, hence highlighting the importance of identifying the type of inter-arrival distributions at the cluster head. In this paper, we present extensive discussions on the assumptions of exponential distributions in WSNs, and present numerical results based on Q-Q plots for estimating the arrival distributions. The work is further extended to understand the impact of end-to-end delay and its effect on inter-arrival time distributions, based on the type of medium access control used in WSNs. Future work is also presented on the grounds that such comparisons based on simple eye checks are insufficient. Since in many cases such plots may lead to incorrect conclusions, demanding the necessity for validating the types of distributions. Statistical analysis is necessary to estimate and validate the empirical distributions of the arrivals in WSNs
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