scholarly journals An MSCN-Based Virtual Computing Cell-Oriented BSM Dissemination Mechanism

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Lei Ye ◽  
Yuping Wu ◽  
Qingwen Han ◽  
Xiaoyuan Zhang ◽  
Lingqiu Zeng ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Real Time ◽  
Network Simulator ◽  
Road Vehicles ◽  
Communication Performance ◽  
Vehicle Density ◽  
Virtual Computing ◽  
Roadside Unit ◽  
Service Migration ◽  
Allocation Approach

With the concept of multiaccess edge computing (MEC) being put forward, Roadside Unit (RSU) is considered as a valid application provider, which not only executes transmission resource allocation and data processing-related computing but also provides real-time applications to road vehicles. However, when fixed roadside nodes communicate with mobile vehicles, the high service migration rate could influence real-time feature of corresponding service. Moreover, vehicle density also affects service performance. Hence, in this paper, a two-processing layer architecture is constructed. A new concept, mobile secondary computing node (MSCN), which is used to compose mobile computing layer, is defined, and the number of MSCN changes dynamically with the vehicle density. Then, MSCN oriented virtual computing cell (VirCC), while corresponding to resource allocation approach and vehicle message dissemination mechanism, is designed. A network simulator (NS-3.28) is employed to investigate the performance of the proposed architecture. The simulation results show that the proposed architecture significantly improves both communication performance and computing efficiency.

SPREAD - A Routing Protocol to Meet End-to-end Adjusted Deadline in Real Time Wireless Sensor Networks

2020 ◽  
Vol 10 (1) ◽  
pp. 63-78
Author(s):  
Neetika Jain ◽  
Sangeeta Mittal
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Real Time ◽  
Routing Protocol ◽  
Resource Constraints ◽  
Wireless Sensor ◽  
Network Simulator ◽  
Packet Delivery ◽  
High Data ◽  
Hard Real Time

Background: Real Time Wireless Sensor Networks (RT-WSN) have hard real time packet delivery requirements. Due to resource constraints of sensors, these networks need to trade-off energy and latency. Objective: In this paper, a routing protocol for RT-WSN named “SPREAD” has been proposed. The underlying idea is to reserve laxity by assuming tighter packet deadline than actual. This reserved laxity is used when no deadline-meeting next hop is available. Objective: As a result, if due to repeated transmissions, energy of nodes on shortest path is drained out, then time is still left to route the packet dynamically through other path without missing the deadline. Results: Congestion scenarios have been addressed by dynamically assessing 1-hop delays and avoiding traffic on congested paths. Conclusion: Through extensive simulations in Network Simulator NS2, it has been observed that SPREAD algorithm not only significantly reduces miss ratio as compared to other similar protocols but also keeps energy consumption under control. It also shows more resilience towards high data rate and tight deadlines than existing popular protocols.

scholarly journals A Novel Rail-Network Hardware Simulator for Embedded System Programming

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 13
Author(s):  
Balaji M ◽  
Chandrasekaran M ◽  
Vaithiyanathan Dhandapani
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
Real Time ◽  
Learning Outcomes ◽  
Real World ◽  
Time Constraints ◽  
Network Simulator ◽  
Practical Applications ◽  
Rail Network ◽  
Knowledge Enhancement

A Novel Rail-Network Hardware with simulation facilities is presented in this paper. The hardware is designed to facilitate the learning of application-oriented, logical, real-time programming in an embedded system environment. The platform enables the creation of multiple unique programming scenarios with variability in complexity without any hardware changes. Prior experimental hardware comes with static programming facilities that focus the students’ learning on hardware features and programming basics, leaving them ill-equipped to take up practical applications with more real-time constraints. This hardware complements and completes their learning to help them program real-world embedded systems. The hardware uses LEDs to simulate the movement of trains in a network. The network has train stations, intersections and parking slots where the train movements can be controlled by using a 16-bit Renesas RL78/G13 microcontroller. Additionally, simulating facilities are provided to enable the students to navigate the trains by manual controls using switches and indicators. This helps them get an easy understanding of train navigation functions before taking up programming. The students start with simple tasks and gradually progress to more complicated ones with real-time constraints, on their own. During training, students’ learning outcomes are evaluated by obtaining their feedback and conducting a test at the end to measure their knowledge acquisition during the training. Students’ Knowledge Enhancement Index is originated to measure the knowledge acquired by the students. It is observed that 87% of students have successfully enhanced their knowledge undergoing training with this rail-network simulator.

SAFER model: Strategic allocation of fundamental epidemic resources

2020 ◽  
Author(s):  
B W Weston ◽  
Z N Swingen ◽  
S Gramann ◽  
D Pojar
Keyword(s):  
Resource Allocation ◽  
Real Time ◽  
Community Based ◽  
Broad Distribution ◽  
Census Tracts ◽  
Milwaukee County ◽  
Strategic Allocation ◽  
Four Quadrant ◽  
Time Resource ◽  
Critical Resources

Abstract Background To describe the Strategic Allocation of Fundamental Epidemic Resources (SAFER) model as a method to inform equitable community distribution of critical resources and testing infrastructure. Methods The SAFER model incorporates a four-quadrant design to categorize a given community based on two scales: testing rate and positivity rate. Three models for stratifying testing rates and positivity rates were applied to census tracts in Milwaukee County, Wisconsin: using median values (MVs), cluster-based classification and goal-oriented values (GVs). Results Each of the three approaches had its strengths. MV stratification divided the categories most evenly across geography, aiding in assessing resource distribution in a fixed resource and testing capacity environment. The cluster-based stratification resulted in a less broad distribution but likely provides a truer distribution of communities. The GVs grouping displayed the least variation across communities, yet best highlighted our areas of need. Conclusions The SAFER model allowed the distribution of census tracts into categories to aid in informing resource and testing allocation. The MV stratification was found to be of most utility in our community for near real time resource allocation based on even distribution of census tracts. The GVs approach was found to better demonstrate areas of need.

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