The programmable hook architecture introduced in Uniswap V4 enables external logic to be executed at predefined lifecycle events within automated market maker (AMM) protocols, enhancing the customizability. However, this design introduces a novel attack surface that conventional static analysis tools are ill-equipped to handle, particularly due to hooks’ context-dependent behavior and lack of publicly available source code. This paper proposes HookScope, a lifecycle-aware dynamic analysis framework for evaluating the structural security of programmable hooks. HookScope defines five runtime threat types (T1-T5) specific to the Uniswap V4 hook model and employs simulation-based testing to detect their manifestation during live contract execution. Risk scores are computed using a CVSS-inspired model that incorporates threat severity, execution context, and system-level impact. Comparative evaluation demonstrates that HookScope identifies threats overlooked by widely-used baseline tools such as Mythril, highlighting the necessity of lifecycle-aware dynamic analysis for programmable DeFi infrastructure. The proposed framework contributes a reproducible, quantifiable approach to threat detection in decentralized protocols and provides a foundation for future research on secure extensibility in AMM-based systems.

Industrial control systems must support both periodic and aperiodic traffic, each with distinct timing and reliability constraints. In particular, aperiodic traffic is classified into three priority levels based on time urgency. While periodic tasks follow fixed schedules, aperiodic tasks are event-driven and require either deadline-aware access or low latency. To address these heterogeneous quality of service (QoS) requirements in duty-cycled, bandwidth-constrained long range (LoRa) networks, we propose QoS-LoRa, a deterministic MAC protocol designed for mixed-criticality traffic. QoS-LoRa integrates three key mechanisms: logical frame partitioning with distributed contention slots, deadline-aware contention window scheduling, and delay-slot-based prioritized access. Together, these components ensure low collision probability, bounded delay, and priority-respecting access across different class tasks. Simulation results show that QoS-LoRa achieves over 95% packet delivery ratio (PDR) for deadline-constrained traffic and over 92% for best-effort traffic, even under 60% aperiodic load. QoS-LoRa significantly outperforms RT-LoRa-LFP and ALOHA-based baselines in PDR, while maintaining end-to-end delay comparable to RT-LoRa-LFP, validating its effectiveness in industrial environments.

We present a new local-search algorithm for the k-median clustering problem. We show that local optima for this algorithm give a (2.836 + ∊)-approximation; our result improves upon the (3 + ∊)-approximate local-search algorithm of Arya et al. [AGK+01]. Moreover, a computer-aided analysis of a natural extension suggests that this approach may lead to an improvement over the best-known approximation guarantee for the problem. The new ingredient in our algorithm is the use of a potential function based on both the closest and second-closest facilities to each client. Specifically, the potential is the sum over all clients, of the distance of the client to its closest facility, plus (a small constant times) the truncated distance to its second-closest facility. We move from one solution to another only if the latter can be obtained by swapping a constant number of facilities, and has a smaller potential than the former. This refined potential allows us to avoid the bad local optima given by Arya et al. for the local-search algorithm based only on the cost of the solution.

Owing to provision of a long-range and robust link, LoRa technology has drawn attention for the use in industrial data collection networks. This article proposes a real-time LoRa protocol that can effectively deal with both periodic and aperiodic data. The slots in a frame are logically partitioned such that they are first scheduled for periodic data by a slot scheduling algorithm, and then, the remaining unscheduled slots are used for event-driven aperiodic data. In this logical frame partitioning, the unscheduled slots appear in an interleaved fashion so that aperiodic tasks can transmit data with low delay and fairness while every periodic task still completes data transmission before the beginning of the next period. To deal with the problems of data collision and traffic congestion for aperiodic data, a two-level collision avoidance scheme is proposed that adopts the notion of a contention window and a delay slot. According to simulation, not only can the proposed protocol guarantee the timely delivery of periodic data but it can also deal with aperiodic data with high reliability, fairness, and low delay, compared with other recent protocols.

Wireless sensor networks (WSNs) can be used for monitoring and control applications in which a server collects data from a work field and provides a service based on the analysis of those data. Such applications require a timely service as well as a reliable data transmission. A smart multichannel cross-layer protocol is proposed that can satisfy the requirements of industrial WSNs. When every sensor node should send data to a server periodically, the protocol not only shortens data acquisition cycle time (DACT) by allowing parallel data transmission using multiple channels but also improves the reliability by avoiding the collisions of control messages using a smart CSMA mechanism. This also can resolve the well-known chronic WSN problems, such as the hidden node, exposed node, and false blocking. In addition, the proposed protocol is reinforced by an adaptive routing and channel selection scheme to improve the reliability of data transmission under the presence of multipath fading, external interference, and industrial noises. By simulation and analysis, it was proven that the proposed protocol could improve DACT, packet delivery ratio, and energy consumption considerably, compared to other protocols. Furthermore, the protocol was successfully applied to a process monitoring system of a smart factory with high reliability in data transmission and a small DACT.

We investigate the query complexity of the fair allocation of indivisible goods. For two agents with arbitrary monotonic utilities, we design an algorithm that computes an allocation satisfying envy-freeness up to one good (EF1), a relaxation of envy-freeness, using a logarithmic number of queries. We show that the logarithmic query complexity bound also holds for three agents with additive utilities and that a polylogarithmic bound holds for three agents with monotonic utilities. These results suggest that it is possible to fairly allocate goods in practice even when the number of goods is extremely large. By contrast, we prove that computing an allocation satisfying envy-freeness and another of its relaxations, envy-freeness up to any good (EFX), requires a linear number of queries even when there are only two agents with identical additive utilities.

Motivated by real-world deployment of drones for conservation, this paper advances the state-of-the-art in security games with signaling. The well-known defender-attacker security games framework can help in planning for such strategic deployments of sensors and human patrollers, and warning signals to ward off adversaries. However, we show that defenders can suffer significant losses when ignoring real-world uncertainties despite carefully planned security game strategies with signaling. In fact, defenders may perform worse than forgoing drones completely in this case. We address this shortcoming by proposing a novel game model that integrates signaling and sensor uncertainty; perhaps surprisingly, we show that defenders can still perform well via a signaling strategy that exploits uncertain real-time information. For example, even in the presence of uncertainty, the defender still has an informational advantage in knowing that she has or has not actually detected the attacker; and she can design a signaling scheme to “mislead” the attacker who is uncertain as to whether he has been detected. We provide theoretical results, a novel algorithm, scale-up techniques, and experimental results from simulation based on our ongoing deployment of a conservation drone system in South Africa.

We investigate the query complexity of the fair allocation of indivisible goods. For two agents with arbitrary monotonic valuations, we design an algorithm that computes an allocation satisfying envy-freeness up to one good (EF1), a relaxation of envy-freeness, using a logarithmic number of queries. We show that the logarithmic query complexity bound also holds for three agents with additive valuations. These results suggest that it is possible to fairly allocate goods in practice even when the number of goods is extremely large. By contrast, we prove that computing an allocation satisfying envyfreeness and another of its relaxations, envy-freeness up to any good (EFX), requires a linear number of queries even when there are only two agents with identical additive valuations.

The task of monitoring a moving phenomenon in an unbounded area using a mobile sensor network (MSN) brings out several challenges due to the high movement speed of phenomenon, the limited sensing/communication capabilities of mobile sensor nodes. To address the challenges and achieve a high weighted sensing coverage, in this paper we propose a monitoring algorithm, namely VirFID-MP (Virtual Force (VF)-based Interest-Driven moving phenomenon monitoring with Mobility Prediction). In VirFID-MP, the movement of phenomenon is first predicted based on its previous movements. Then, the predicted information is used to determine a global virtual force, which is utilized to speed up the MSN toward the moving phenomenon. Simulation results show that VirFID-MP outperforms original VirFID in terms of weighted coverage efficiency, when the MSN monitors a moving phenomenon.

Abstract In this paper, we study mobile sensor network (MSN) architectures and algorithms for monitoring a moving phenomenon in an unknown and open area using a group of autonomous mobile sensor (MS) nodes. Monitoring a moving phenomenon involves challenges due to limited communication/sensing ranges of MS nodes, the phenomenon’s unpredictable changes in distribution and position, and the lack of information on the sensing area. To address the challenges and meet the objective of the maximization of weighted sensing coverage, we propose a novel scheme, namely VirFID (Virtual Force (VF)-based Interest-Driven moving phenomenon monitoring). In VirFID, MS nodes move toward the positions where more interesting sensing data can be obtained by utilizing the virtual force, which is calculated based on the distance between MS nodes and sensed values in the area of interest. MS nodes also perform network-wise information sharing to increase the weighted sensing coverage. Depending on the level of information used, three variants of VirFID are evaluated: VirFID-LIB (Local Information-Based), VirFID-GHL (Global Highest and Lowest), and VirFID-IBN (Interests at Boundary Nodes). In addition, an analytical model for estimating MSN speed is designed. Simulations are performed to compare the performance of three VirFID variants with other approaches. Our simulation results show that VirFID algorithms outperform other schemes in terms of the weighted coverage efficiency, and VirFID-IBN achieves the highest weighted coverage efficiency among VirFID variants.

Summary In case that we build a context‐aware computing‐based Safety Monitoring and Control System (SMOCS) that monitors the safety of the workers, many sensor devices with different data rates are distributed in the target field. Based on these context data, the SMOCS judges the safety of the working environment primarily. If it perceives a dangerous sign, it requests additional bursty data such as still image or video streaming from a particular sensor device in order to confirm the situation. Because these bursty data have to be delivered to the server reliably with time constraints, it is challengeable to process those data with limited energy and bandwidth. In this paper, we propose an efficient approach to deliver bursty data reliably by reserving time slots to transmit the required packets on all the paths from the selected multimedia nodes to the server. The nodes that are not on the selected paths are put into sleep mode to conserve energy during the transmission of bursty data. We evaluate the proposed approach by conducting experiments using the indoor test bed that consists of 30 sensor communication devices. The experimental results show that the proposed approach can satisfy the requirements of multimedia applications well. Copyright © 2014 John Wiley & Sons, Ltd.

In ad hoc networks, wireless links are subject to a low quality due to time-varying channel properties, node mobility, and obstacles. Such low quality wireless links lead to the degraded performance of the end-to-end data transfer service, which also result in less applicability of ad hoc networks to practical deployment. In order to address the problem of low quality wireless links and provide a required quality for end-to-end data transfer services, we propose a novel routing and relaying architecture that exploits controllable mobility of robotic relays, namely RoCoMAR (Robots' Controllable Mobility Aided Routing), which repeatedly reinforces wireless links with the main objective of maximizing the network throughput. RoCoMAR first identifies the lowest quality link and replaces it with high quality links that are created by re-locating a robotic relay in an optimal position. The simulation results show that RoCoMAR outperforms existing ad hoc routing protocols in terms of network throughput and end-to-end delay.

A stability of routing path is of a great importance for a reliable communication in mobile ad hoc networks. We propose a novel source routing protocol that establishes a group path with virtual multiple paths to enable a robust communication. The entire mobile nodes form a disjoint set of clusters: Each has its clusterhead as a cluster leader and all the members in the same cluster are assigned an identical cluster label by its clusterhead. A group path is a sequence of cluster labels instead of nodes and the nodes with the same label collaborate to deliver packets to a node with next label on the group path. We prove by resorting to simulation that our proposed protocol outperforms the existing key routing protocols, even for a network with a high mobility of node and a high traffic.

We propose a tree-based routing protocol (TBRP) with node mobility management technique for integrated mobile ad hoc and infrastructure networks. A suite of network management protocols build and maintain a network architecture in the form of small-sized trees, each starting from a node that can directly communicate with a gateway. Each node in a tree keeps track of information for its descendent nodes. A new node registers with a foreign agent along a tree path without resorting to an inefficient flooding. We also devise an efficient routing protocol that exploits tree information where route discovery does not use a flooding, either. We examined the proposed protocol for its applicability and got a promising result, even with high network traffic.

Embedded music software for music embedded system is designed and analyzed by applying the DARTS (design approach for real-time systems) that appropriately deals with concurrent tasking architecture. The existing approaches for the music application have not considered a real-time multitasking model. So, it suffers from more complexity and less flexibility in design as well as lack of predictability for the timely execution of critical tasks. In this paper, we design a new concurrent tasking architecture for a real-time embedded music system and examine its feasibility, wherein all real-time tasks are examined for satisfying their respective constraints. The design is implemented on the Linux based Xhyper272 Board that uses the Intel Bulverde microprocessor.