Multiple Destinations Research Articles

Routing and secret key assignment for secure multicast services in quantum satellite networks

Multicast is an important service type in both terrestrial and space communication networks but has security issues because more than one destination node can receive information. Point-to-point quantum key distribution can be achieved end-to-end over long distances by using a quantum satellite (e.g., Micius) as a relay node. Hence, how to provide secret keys for remote multicast services and efficiently distribute secret keys between the source node and multiple destination nodes for long-distance secure multicast services (SMSs) has become a critical problem. In this paper, a quantum satellite network with a special node structure is designed to complete point-to-multipoint key distribution, and a point-to-multipoint satellite relay scheme is proposed. The weight information of the link is dynamically described by the method of auxiliary topology, and a satellite relay tree is constructed. Finally, this paper proposes a satellite relay algorithm for multicast services to route and allocate key resources to solve the problem of long-distance point-to-multipoint key relay and improve the success probability of multicast service requests. Simulation results show that the proposed algorithm can improve the success probability of SMS requests by about 51.32% in a static scenario and 17.33% in a dynamic scenario.

Use of the "Future Life Map" exercise to improve awareness of career options and opportunities in underrepresented minority undergraduate students pursuing STEM careers.

ObjectivesThere has long existed significant underrepresentation of minority students in STEM training and careers. Ongoing efforts to improve opportunities and participation for underrepresented minority students have focused on multiple areas, from increased funding to early exposure to research in STEM. We developed the novel Future Life Map career planning exercise with the goal of contributing to this multi-faceted approach. The exercise emphasizes on the consideration of multiple potential career destinations and routes to those destination. The exercise was designed with the goal of improving participant awareness of options and career planning self-efficacy to improve success and retention of underrepresented minority student participation and retention in STEM.MethodsWe implemented the Future Life Map exercise with 2 separate groups of under-represented minority undergraduate students pursuing careers in STEM. Participants then completed an anonymous survey to evaluate the exercise and describe the value they derived from completing the Future Life Map.ResultsThe exercise presentation and its supporting documents were highly rated by participants with >81% of respondents rating it as “very informative” (4 or 5 on a 5-point Likert Scale). Participants reported that they were very likely to recommend the exercise to others (25 of 27 participants) and were likely to repeat the activity for their own future decision making (22 participants). Themes that emerged from participant reporting of the value of the exercise were: increased awareness of career and training options, improved understanding of the research required to make informed career/life decisions, and new awareness of specific information about career options under consideration.ConclusionThe Future Life Map exercise was successful in improving participant awareness of career options, career planning ability, and helped participants to feel more empowered. This is likely of particular benefit for improving participation and retention of under-represented minority students pursuing careers in STEM.

The RapidIO Routing Strategy Based on the Double-Antibody Group Multi-Objective Artificial Immunity Algorithm.

The RapidIO standard is a packet-switching interconnection technology similar to the Internet Protocol (IP) conceptually. It realizes the high-speed transmission of RapidIO packets at the transport layer, but this greatly increases the probability of network blocking. Therefore, it is of great significance to optimize the RapidIO routing strategy. For this problem, this paper proposes a Double-Antibody Group Multi-Objective Artificial Immune Algorithm (DAG-MOAIA), which improves the local search and global search ability of the population by adaptive crossover and adaptive mutation of the double-antibody groups, and uses co-competition of multi-antibody groups to increase the diversity of population. Through DAG-MOAIA, an optimal transmission path from the source node to multiple destination nodes can be selected to solve the Quality Of Service (QoS) problem during data transmission and ensure the QoS of the RapidIO network. Simulation results show that DAG-MOAIA could obtain high-quality solutions to select better routing transmission paths, and exhibit better comprehensive performance in all simulated test networks, which plays a certain role in solving the problem of the RapidIO routing strategy.

Exploring changes in individuals travel behaviour after bus Rapid Transit implementation in Dar es Salaam

The use of Informal Public Transport (IPT; i.e., minibuses, motorcycles, and tricycles) for activity participation in Dar es Salaam is associated with mobility difficulties, e.g., traffic congestion, unscheduled services, and lack of safety of the journey. The introduction of the Bus Rapid Transit (BRT) in May 2016 aimed at reducing mobility difficulties by improving public transport (PT) with scheduled services and fully dedicated lanes to improve access to the Central Business District. This study compares individuals' travel behaviour before and (2 years) after BRT implementation using a GPS-app to explore changes in spatial mobility demands, i.e., (new) visited places, frequency of travel, trip distances, and departure times. Short surveys were used to record the socio-demographic characteristics. Results: the use of IPT remained a necessary means of transport for low-income individuals to commute outside the BRT corridor in multiple destinations, as the use of the BRT route is spatially limited. The new BRT system had become the main option for trips conducted to fixed destinations along the corridor and within service hours. The spatial mobility patterns showed that individuals are now adding BRT to their trip chaining, enabling them to access amenities, make more trips and travel farther distances. The results provide insights for transportation planners who tend to focus mainly on BRT as the only solution for all mobility demands. Each transport system has its own spatial mobility benefits to offer. An integrated PT within a framework of a multimode system is vital for inclusive mobility.

Optimization of Distribution Cost (a Case study in PT. Zamrud Bumi Indonesia)

PT. Zamrud Bumi Indonesia is a manufacturing company engaged in the processing of multipurpose liquid organic agricultural fertilizer branded Power Bumi. Distribution from warehouses to destinations that vary in distance resulted in different distribution cost budgets. Transportation models can help solve the problem of distributing products from multiple warehouses to multiple destination cities and reduce total distribution costs. This study aims to find out the total minimum cost of distribution by using the Least Cost method as the initial solution and knowing the test results of MODI method as the optimum solution at PT. Zamrud Bumi Indonesia. The results of this study showed that before using the Transportation Method, the company incurred a distribution fee of Rp. 11.600.000,- in December 2020, after using the Least Cost transportation method as the initial solution of distribution costs incurred in the amount of Rp. 9.981.250,- and modi transportation method as the optimum test resulted in the same value of Rp. 9,981,250. So the company saves distribution costs of Rp. 1.618.750,- every month

Demultiplexing sound in stacked valley-Hall topological insulators

Demulitplexing is used to connect data or signals from one single channel stream to multiple destinations. The streams may be additionally divided through their frequency, polarizations, angular momentum, etc. Here, we show how one is able to demultiplex sound waves at different physical positions and frequency components by employing stacked valley-Hall topological insulators made of merged triangular rigid scatterers. By tuning their two relative angles, we are able to break or restore the underlying lattice symmetry within two topologically independent band gaps. Thus, we experimentally stacked various individually tuned valley-Hall insulators to enable spectrally specific radiated sound to be routed to a particular destination via scattering-immune valley-projected edge states. We foresee that these findings will advance further studies in condensed matter physics, classical wave physics, but also in technological areas of communication by capitalizing on unconventional valley-Hall physics.

Optimization Problem of Pricing and Seat Allocation Based on Bilevel Multifollower Programming in High-Speed Railway

This paper studies the multistage pricing and seat allocation problems for multiple train services in a high-speed railway (HSR) with multiple origins and destinations (ODs). Taking the maximum total revenue of all trains as the objective function, a joint optimization model of multistage pricing and seat allocation is established. The actual operation constraints, including train seat capacity constraints, price time constraints in each period, and price space constraints among products, are fully considered. We reformulate the optimization model as a bilevel multifollower programming model in which the upper-level model solves the seat allocation problem for all trains serving multiple ODs in the whole booking horizon and the lower optimizes the pricing decisions for each train serving each OD in different decision periods. The upper and lower are a large-scale static seat allocation programming and many small-scale multistage dynamic pricing programming which can be solved independently, respectively. The solving difficulty can be significantly reduced by decomposing. Then, we design an effective solution method based on divide-and-conquer strategy. A real instance of the China’s Wuhan-Guangzhou high-speed railway is employed to validate the advantages of the proposed model and the solution method.

A double jeopardy: COVID-19 impacts on the travel behavior and community living of people with disabilities.

The COVID-19 pandemic response has had a significant impact on the general population’s ability to participate in their communities. Individuals with disabilities, an already socially disadvantaged population, are more vulnerable to and have likely been disproportionately impacted by COVID-19 response conditions. Yet, the extent to which daily community living activities of people with disabilities have been impacted is unknown. Thus, this study assesses their travel behavior and community living during the COVID-19 pandemic conditions compared with those of the general population during the same period.A web survey was conducted using Qualtrics’s online panel data (respondents included 232 people with disabilities and 161 people without disabilities). Regression models found that people with disabilities reduced their daily travel to a greater extent but at varying degrees, depending on the destination types and travel modes. Reductions in taxi rides (including ride-hailing services) were most significant among people with cognitive and sensory (vision and hearing) disabilities. By place type, cognitive disability was associated with a trip reduction for multiple destination types—grocery, restaurants, outdoor recreation, indoor recreation, and healthcare providers. Findings from this study could contribute to decision- and policy-making in planning, transportation, and community services during the remainder of the COVID-19 pandemic, in future major public health crises, as well as post-COVID, because the adjustments in travel behavior and community living might be longer-term.

Transnational Cross-Border Family Ties: Diasporic Lives of Bangladeshis in Italy and Beyond

The scope of this paper is to gain a better understanding of how Bangladeshi migrants in Italy maintain transnational family attachments, across multiple destinations, with the home country as well as with several host countries. The data comes from fieldwork in Northeast Italy. Research methods include in-depth interviews and participant observation. The findings reveal that a high proportion of Bangladeshi migrants maintain a variety of transnational and diasporic ties with their family and friends living in the country of origin and different European countries. These include family obligations, remittances, establishing businesses back home, visits and communication. They also preserve their national identity in this host society by maintaining cultural ways of belonging and through religious practices and involvement in Bangladeshi politics. The findings have also shown that Italian Bangladeshi families work to foster transnational family ties among the new generations born in Italy, who have little knowledge of their ancestral country. On a final note, this paper argues that transnational connections with the homeland play an important role in shaping the diasporic lives of Bangladeshis in Italy.

System Reliability of a Stochastic Multiple-Origin-Destination Tourism Transport Network With Tardiness

As transport is a vital component in the modern tourism industry, determining reliable-performance tourism transport networks is critical for tour operators and travel agencies. The performance of a tourism transport network in this study is investigated by evaluating system reliability, which is the probability of successfully transporting requested passengers between multiple origins and multiple destinations within a time constraint when tardiness may occur. A stochastic multiple-origin-destination tourism transport network with tardiness (SMTNT) is formulated for system reliability evaluation. Identify all minimal travel paths (MTP) and corresponding maximum tardiness vectors that successfully connect each origin–destination pair under a time constraint. System reliability is derived from all flow vectors enabling delivery via MTPs a requested number of passengers at different tardiness levels. The proposed algorithm is successful in handling a combination of time constraints in the case of tardiness with multiple origin–destination pairs. Furthermore, it helps travel agencies obtain an insight into the performance of their SMTNT. An example describing the working of the proposed algorithm with an analysis of system reliability is provided. The results of the study can be used for improving the algorithm in the future.

A collective neurodynamic approach for solving distributed system optimum dynamic traffic assignment problems

In this paper, the traditional system optimum dynamic traffic assignment (SO-DTA) problem is solved by distributed multi-agent dynamics. The goal of SO-DTA is to optimally control the route choice of each user to minimize the total travel time by all users over the assignment time period. It is beneficial for reducing the congestion of the traffic network with time-varying demand. Different from the traditional SO-DTA which is formulated and solved in a centralized scheme, we aim at solving it from a multi-agent perspective in a communication network. Based on the cell transmission model, two connector-based relaxed SO-DTA models are provided in a multi-agent system framework for the traffic network with a single destination and multiple destinations, respectively. In the provided models, each cell connector is treated as an agent, which could exchange information with its adjacent connectors to accomplish the system optimization objective. Then, a collective neurodynamic system equipped with the proposed distributed protocol is used to solve general network optimization problems including the above SO-DTA models as special cases. The convergence analysis is further given for the proposed algorithm. Numerical studies over various traffic networks are presented to show the effectiveness of the proposed method.

Non-Linear Energy Harvesting in RIS-Assisted URLLC Networks for Industry Automation

A reconfigurable intelligent surface (RIS)-assisted wireless communication system with non-linear energy harvesting (EH) and ultra-reliable low-latency constraints is considered for its possible applications in industrial automation. A distant data-center (DC) communicates with the multiple destination machines with the help of a full-duplex (FD) server machine (SM) and RIS. Assuming the deficiency of enough transmission power at the FD-SM, the SM is considered in the near vicinity of the destinations in the industry to forward the data received from the distant DC. The reception at SM is assisted by the RIS and a non-linear hybrid power-time splitting (PTS) based EH receiver architecture is adopted to extend the lifespan of SM, thus increasing network lifetime. The scheduling of multiple destinations is done by SM based on the considered selection criteria namely, random (RND) scheduling, absolute (ABS) channel-power-based (CPB) scheduling and normalized (NRM) CPB scheduling. The end-to-end performance of the considered FD RIS-assisted network is analyzed, and the expressions for the block error rate (BLER) for all scheduling schemes are derived. Moreover, the effects of number of RIS elements, packet size, channel uses on the system performance are analyzed for the considered ultra-reliable and low-latency communication (URLLC) network. The scheduling fairness of all the scheduling schemes is also analyzed to study the performance-fairness trade-off. The derived analytical results are verified through Monte-Carlo simulations.

Freeway network design with exclusive lanes for automated vehicles under endogenous mobility demand

Automated vehicles (AV) have the potential to provide cost-effective mobility options along with overall system-level benefits in terms of congestion and vehicular emissions. Additional resource allocation at the network level, such as AV-exclusive lanes, can further foster the usage of AVs rendering this mode of travel more attractive than legacy vehicles (LV). However, it is necessary to find the crucial locations in the network where providing these dedicated lanes would reap the maximum benefits. In this study, we propose an integrated mixed-integer programming framework for optimal AV-exclusive lane design on freeway networks which accounts for commuters’ demand split among AVs and LVs via a logit model incorporating class-based utilities. We incorporate the link transmission model (LTM) as the underlying traffic flow model due to its computational efficiency for system optimum dynamic traffic assignment. The LTM is modified to integrate two vehicle classes namely, LVs and AVs with a lane-based approach. The presence of binary variables to represent lane design and the logit model for endogenous demand estimation results in a nonconvex mixed-integer nonlinear program formulation. We propose a Benders’ decomposition approach to tackle this challenging optimization problem. Our approach iteratively explores possible lane designs in the Benders’ master problem and, at each iteration, solves a sequence of system-optimum dynamic traffic assignment problems in an attempt to find fixed-points representative of logit-compatible demand splits. The proposed approach is implemented on three hypothetical freeway networks with single and multiple origins and destinations. Our numerical results reveal that the optimal lane design of freeway network is non-trivial while accounting for endogenous demand of each mode.

IoT network traffic analysis: Opportunities and challenges for forensic investigators?

As IoT devices become more incorporated into our daily lives, their always on approach makes them an ideal source of evidence. While these devices should use encryption to protect sensitive information, in reality this is not always the case e.g. some expose sensitive data like credentials in cleartext. In this paper, we have conducted an extensive analysis on the communications channels of 32 IoT consumer devices. Our experiments consisted of four main parts; first we carried out a port scan to determine if any ports can be exploited and thus gain remote access. Second, we looked at whether any of the devices used encryption and if not what type of content was exposed. Third, we used the network traffic ‘metadata’ to identify the destination the data terminated. Finally, we examined the communication between the mobile app and the cloud to see if it can be easily exploited using a proxy server. Our findings show that the majority of devices have remote access unavailable. We found the Shannon entropy test a useful pre-test in identifying unencrypted content. Although many devices encrypted their data, we found several in particular smart cameras would send data in cleartext when they detected motion or during updates. We found the majority of data transverses to the US and stored on Amazon servers with most devices contacting multiple destination. Lastly, we discovered many of the IoT device's mobile apps can be easily exploited using a HTTP Proxy.

Age and Energy Tradeoff for Multicast Networks With Short Packet Transmissions

Age of information (AoI) and energy efficiency (EE), as two important performance metrics in status update systems, usually cannot be simultaneously optimized. This paper investigates the age and energy tradeoff for multicast networks with retransmissions, where each sensed status update is encoded as a short blocklength packet and is broadcasted to multiple destinations via independent and identically distributed error-prone channels. By considering the stopping threshold, the average AoI and EE expressions for stopping at earliest- <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> , stopping at preselected- <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> , and wait-for-all schemes are derived as a function of the packet length. On this basis, the average AoI-EE ratio is introduced and is minimized to trade off age and energy by optimizing the packet length. Numerical results indicate that among the three schemes, earliest- <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> scheme attains the minimum AoI when the packet length is small, and preselected- <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> scheme attains the maximum EE when the packet length is large. An optimal packet length can always be found for each scheme to minimize age-energy ratio. Moreover, the selection of stopping threshold <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> will also impact the age and energy performance.

Multi-Destination Path Planning Method Research of Mobile Robots Based on Goal of Passing through the Fewest Obstacles

In order to effectively solve the inefficient path planning problem of mobile robots traveling in multiple destinations, a multi-destination global path planning algorithm is proposed based on the optimal obstacle value. A grid map is built to simulate the real working environment of mobile robots. Based on the rules of the live chess game in Go, the grid map is optimized and reconstructed. This grid of environment and the obstacle values of grid environment between each two destination points are obtained. Using the simulated annealing strategy, the optimization of multi-destination arrival sequence for the mobile robot is implemented by combining with the obstacle value between two destination points. The optimal mobile node of path planning is gained. According to the Q-learning algorithm, the parameters of the reward function are optimized to obtain the q value of the path. The optimal path of multiple destinations is acquired when mobile robots can pass through the fewest obstacles. The multi-destination path planning simulation of the mobile robot is implemented by MATLAB software (Natick, MA, USA, R2016b) under multiple working conditions. The Pareto numerical graph is obtained. According to comparing multi-destination global planning with single-destination path planning under the multiple working conditions, the length of path in multi-destination global planning is reduced by 22% compared with the average length of the single-destination path planning algorithm. The results show that the multi-destination global path planning method of the mobile robot based on the optimal obstacle value is reasonable and effective. Multi-destination path planning method proposed in this article is conducive to improve the terrain adaptability of mobile robots.

Proof of accumulated trust: A new consensus protocol for the security of the IoV

The Internet of Vehicles (IoV) is a distributed network that enables vehicles to connect to each other and to various infrastructure and smart devices, in order to exchange data and provide important services. The highly dynamic environment of the IoV offers a lot of opportunities but at the same time makes the network susceptible to a large number of security attacks. In this paper, we propose a framework that comprises a private blockchain model to secure the transactions that are generated by vehicles. Our model makes use of our proposed Proof of Accumulated Trust (PoAT) mechanism that selects specific RSUs to become blockchain miners based on their accumulated trust. In addition, the proposed system introduces a smart redundancy method in which each vehicle and RSU sends a transaction to multiple destinations, in order to avoid the situation when one or more IoV nodes are compromised. We conduct extensive experiments in which we compare our system to two recent blockchain-based security frameworks for the IoV. The simulation results illustrate the superiority of our system in terms of attack detection rate, blockchain generation time, and network overhead traffic.

Comprehensive Effects of Short-Term Rental Platforms Across Hotel Types in U.S. and International Destinations

In recent years, short-term rental platforms in the lodging sector, including Airbnb, VRBO, and HomeAway, have received extensive attention and emerged as potentially alternative suppliers of services traditionally provided by established commercial accommodation providers, that is, hotels. Short-term rentals have dramatically increased the available supply of rooms for visitors to multiple international destinations, potentially siphoning demand away from hotels to short-term rental businesses. In a competitive market, an increase in supply with constant demand would negatively influence incumbent service providers. In this article, we examine the substitution effects of short-term rental supply on hotel performance in different cities around the world. Specifically, we comprehensively investigate the substitution effects of short-term rental supply on hotel performance based on hotel class, location type, and region. Furthermore, we segment the short-term rental supply based on its types of accommodations, that is, shared rooms, private rooms, and entire homes, and both examine and quantify the differential effects of these types of short-term rentals on different types of hotels. This study offers a comprehensive analysis regarding the impact of multiple short-term rental platforms on hotel performance and offers both conceptual and practical insights regarding the nature and extent of the effects that were identified.

Destination images of ecotourism in Maluku: A marketing perspective

The tourism industry has developed very rapidly in the last decade. Various types of tourism grow according to the wishes and preferences of tourists. The current kind of tourist segmentation is very diverse, so it makes multiple destinations with specific markets. One of them is ecotourism. Ecotourism develops and combines three aspects of tourism: natural sustainability, community empowerment, and increasing environmental awareness. This research discusses ecotourism from a different perspective, that is, marketing. Ecotourism is seen as a product that must be marketed by promoting marketing concepts. So far, we rarely encounter organizing tourist events in enhancing the image of ecotourism destinations because they conflict with natural sustainability. Several marketing concepts are needed to strengthen the economic aspect, including social media marketing and tourism events. The purpose of the whole idea is aimed at improving the image of the destination. This research uses quantitative analysis with Partial Least Square analysis tools. Respondents in this study amounted to 100 tourists. R-Square 0.45 shows that social media marketing and tourist events are also important and can build a destination image of an ecotourism destination.

A novel Network Partitioning Attack against Routing Protocol in Internet of Things

The Internet of Things (IoT) environment comprises large scale deployment of constrained devices like RFIDs and sensors making routing an essential requirement. These constrained devices are part of the Low power and Lossy Networks (LLNs) in the IoT. The Internet Engineering Task Force standardized IPv6 Routing Protocol for Low power and Lossy Networks (RPL) as the routing protocol for LLNs in IoT. IoT-LLNs are organized as multiple Destination Oriented Directed Acyclic Graphs (DODAGs). The root node in the DODAG organizes and maintains the DODAG through broadcast based configuration information dissemination process. The root node also connects the various nodes in the DODAG to the rest of the IoT network. Hence, for any node in the IoT-LLN, connectivity with the root node is important. We present a novel Network Partitioning Attack (NPA) scenario against RPL in IoT-LLNs wherein a malicious node segregates a section of the IoT-LLN from the root node and thus from the rest of the IoT network. In this paper, we discuss in-depth the vulnerabilities of RPL, which result in the proposed Network Partitioning Attack. We present an analytical model to demonstrate the impact of the attack on the performance of the routing protocol and validate the model through simulation. We also suggest mechanisms to mitigate the attack.