Several studies in recent years have considered the use of mobile elements for data gathering in wireless sensor networks, so as to reduce the need for multi-hop forwarding among the sensor nodes and thereby prolong the network lifetime. Since, typically, practical constraints preclude a mobile element from visiting all nodes in the sensor network, the solution must involve a combination of a mobile element visiting a subset of the nodes (cache points), while other nodes communicate their data to the cache points wirelessly. This leads to the optimization problem of minimizing the communication distance of the sensor nodes, while keeping the tour length of the mobile element below a given constraint. Several algorithms in existing literature have tackled this problem by separating the construction of the mobile element tour from the computation of the forwarding trees to the cache points. In this paper, we propose a new algorithm that alternates between these phases and iteratively improves the outcome of each phase, based on the result of the other. We compare the resulting performance of our algorithm with that of previous work, and show that it closes a considerable portion of the gap from the theoretical optimal solution.

The usage of blockchain technology has been significantly expanded with smart contracts and blockchain oracles. While smart contracts enables to automate the execution of an agreement between untrusted parties, oracles provide smart contracts with data external to a given blockchain, i.e., off-chain data. However, the validity and accuracy of such off-chain data can be questionable that compromises the transparency and immutability chacteristics of blockchain. Despite many studies on the trustworthiness of blockchain oracles, more precisely, off-chain data, their solutions are often ‘short-sighted’ and dependent on binary decisions. In this paper, we present a novel graph-based profiling method to determine the trustworthiness of blockchain oracles. We construct a graph with oracles as nodes and cumulative average discrepancies of validity and accuracy of data as edge weights. Our profiling method continues to update the graph, edge weights in particular, to distinguish trustworthy oracles. Clearly, this discourages the provision of false and inaccurate data. We have conducted an evaluation study to see the effectiveness of our proposed method, in which we have run the experiments utilizing the Ethereum network. Additionally, we have also calculated the cost of running these experiments. Consequently, our experiment results show that the proposed method achieves around 93% accuracy in identifying the trustworthiness of data sources.

We consider the problem of gathering data from a sensor network using mobile elements. In particular, we consider the case where the data are produced by measurements and need to be delivered to a predefined sink within a given time interval from the time the measurement takes place. Mobile elements travel the network in predefined paths, collect the data from the nodes, and deliver them to the sink. Each node must be visited by a mobile element that must then reach the sink within the given time constraint. The goal is to plan the paths for the mobile elements that minimize the total length travelled. Several variations of this problem have been considered in existing literature. We propose an algorithmic solution that builds node-disjoint tours that always include the sink, cover the network, and optimize the total length travelled. We provide an integer linear programming formulation for the problem, and propose two novel heuristics for building the tours. We evaluate the performance of our algorithm by comparing it to the optimal solution as well as to an alternative heuristic, commonly used in related time-window vehicle routing problems, and demonstrate the superior performance of our approach.

Many applications in science and engineering become increasingly complex and large scale. These applications often consist of a large number of precedence-constrained tasks forming workflows represented by directed acyclic graph (DAG). In recent years, cloud computing has greatly leveraged the elastic and cost-efficient deployment of these applications. However, their effective deployment is largely dependent on the scheduling algorithm adopted. Most existing workflow scheduling algorithms are designed to optimize deadline or budget/cost, i.e., one being the objective and the other being constraint. In this paper, we present the Partitioning-Based Workflow Scheduling (PBWS) algorithm, which liberates the user from explicitly setting the upper bound of deadline and cost. Instead, PBWS adopts a slack parameter that controls the tradeoff point between deadline and cost. In particular, PBWS partitions a workflow into a number of small task graphs (or simply partitions) for which the granularity of such partitions is determined by the slack parameter. Each of these partitions is then matched with the best performing cloud resource in terms of both the overall execution time (makespan) and cost. The size of partitions may change by rearranging tasks between different partitions for the optimization of resource assignment. Our experimental results show that our PBWSalgorithm outperforms two existing algorithms in terms of cost by a large margin with little overhead on makespan.

Blockchain technology has increasingly drawn the attention of governments seeking to modernize public services through transparent, secure, and efficient digital infrastructures. Drawing on case studies from diverse regions, including the UAE, Estonia, Georgia, Colombia, and multiple Gulf Cooperation Council (GCC) nations, this systematic review synthesizes implementation patterns across domains such as land administration, digital identity, procurement, and intergovernmental payments. The critical analysis highlights blockchain’s capacity to establish tamper-evident records, automate verification, and reduce administrative overhead while also addressing technical and institutional factors that shape its impact. Outcomes across successful deployments suggest that benefits are most pronounced when blockchain aligns with real governance needs and is supported by robust legal and digital infrastructure. This review also identifies key barriers to adoption, including interoperability challenges, regulatory uncertainty, limited technical capacity, and resistance to organizational change. Notably, this review highlights a critical but underexplored dimension involving the need for public accountability not only in service delivery but also in the governance of blockchain systems themselves. By examining real-world use cases alongside technical and policy frameworks, this review advances a deeper understanding of blockchain’s role in reshaping public administration and sets a research agenda for building more trusted, auditable, and inclusive digital government systems.

As a critical factor in ensuring the growth of the electronic auction (e-auction) domain, the privacy and security of the participants (sellers and buyers) must always be guaranteed. Traditionally, auction data, including participant details, are stored in a third party (auctioneer) database. This leads to a high risk of a single point of failure in terms of privacy and security. Toward this end, blockchain technology has emerged as a promising decentralized communication paradigm to address such risks. This paper presents a blockchain-based auction framework as a decentralized e-auctioning framework for location-aware services. In particular, the framework consists of three components: pre-auctioning, main auctioning, and post-auctioning processes with four algorithms. Our primary focus is on location-aware services, such as storage space rental, apartment rental, transport hire, and parking space rental. The trading volumes are expected to be high; hence, simplifying the design is a crucial requirement. In addition to the benefits of eliminating the centralized entity (the auctioneer), fees are redistributed among participants as rewards. Further, we incorporate a service quality monitoring method that ranks the services provided by participants. This ranking allows participants to determine the rank of other participants with whom they wish to trade. We have conducted several experiments to evaluate the proposed framework’s cost feasibility and to ensure the ease of the business flow.