Computational and Location Aware Middleware to Enable Edge Computing in Mobile Devices

2021 ◽  
Author(s):  
Sweta Jaiswal ◽  
Jamsheed Manja Ppallan ◽  
Karthikeyan Arunachalam ◽  
Shiva Souhith Gantha
Keyword(s):  
Mobile Devices ◽  
Edge Computing ◽  
Location Aware

Tracking of Wearable IoT Devices Through WAP Using Intelligent Rule-Based Location Aware Approach

2021 ◽  
Vol 20 (Supp01) ◽  
pp. 2140005
Author(s):  
L. Sai Ramesh ◽  
S. Shyam Sundar ◽  
K. Selvakumar ◽  
S. Sabena
Keyword(s):  
Mobile Devices ◽  
Task Completion ◽  
End User ◽  
Access Points ◽  
The Public ◽  
Location Aware ◽  
Unique Identity ◽  
Iot Devices ◽  
Public Environment ◽  
Specific Scenario

Usage of the internet is increasing in the daily life of humans due to the need for speedy task completion for their daily services. Most of the living time is spent in some indoor environment which provides WiFi which is the basic need of internet connectivity using Wireless Access Points (WAP). Nowadays, most of the devices are IoT-based ones, which connect with the outer world through the access points in the existing environment. The wearable IoT devices may be misplaced somewhere and we need a specific scenario which helps to identify the misplaced mobile devices based on access points where they are connected by their unique identity such as MAC address. Most of the time, unrestricted WiFi access provided in the public environment is used by the end-user. In that scenario, the tracking of misplaced mobile devices is creating an issue when the WiFi is in switch-off mode. This paper proposes a technique for tracking a mobile device by using a location-aware approach with KNN and intelligent rules by tracking the channel accessed by the user to find the misplaced path by examining the device connected WAP positions.

scholarly journals ECLB: Edge-Computing-Based Lightweight Blockchain Framework for Mobile Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Qingqing Xie ◽  
Fan Dong ◽  
Xia Feng
Keyword(s):  
Mobile Devices ◽  
Security Analysis ◽  
Edge Computing ◽  
Mobile Systems ◽  
Superior Performance ◽  
Consensus Protocol ◽  
Open Problems ◽  
Blockchain Technology ◽  
Natural Solution ◽  
And Performance

The blockchain technology achieves security by sacrificing prohibitive storage and computation resources. However, in mobile systems, the mobile devices usually offer weak computation and storage resources. It prohibits the wide application of the blockchain technology. Edge computing appears with strong resources and inherent decentralization, which can provide a natural solution to overcoming the resource-insufficiency problem. However, applying edge computing directly can only relieve some storage and computation pressure. There are some other open problems, such as improving confirmation latency, throughput, and regulation. To this end, we propose an edge-computing-based lightweight blockchain framework (ECLB) for mobile systems. This paper introduces a novel set of ledger structures and designs a transaction consensus protocol to achieve superior performance. Moreover, considering the permissioned blockchain setting, we specifically utilize some cryptographic methods to design a pluggable transaction regulation module. Finally, our security analysis and performance evaluation show that ECLB can retain the security of Bitcoin-like blockchain and better performance of ledger storage cost in mobile devices, block mining computation cost, throughput, transaction confirmation latency, and transaction regulation cost.

Collaborative Mapping and GIS

2010 ◽  
pp. 388-399 ◽  
Author(s):  
Edward Mac Gillavry
Keyword(s):  
Web Services ◽  
Mobile Devices ◽  
Real World ◽  
Information Infrastructure ◽  
Geographic Information ◽  
Web Technologies ◽  
Location Aware ◽  
Collaborative Mapping ◽  
Machine Readable ◽  
Complementary And Alternative

The collection and dissemination of geographic information has long been the prerogative of national mapping agencies. Nowadays, location-aware mobile devices could potentially turn everyone into a mapmaker. Collaborative mapping is an initiative to collectively produce models of real-world locations online that people can then access and use to virtually annotate locations in space. This chapter describes the technical and social developments that underpin this revolution in mapmaking. It presents a framework for an alternative geographic information infrastructure that draws from collaborative mapping initiatives and builds on established Web technologies. Storing geographic information in machine-readable formats and exchanging geographic information through Web services, collaborative mapping may enable the “napsterisation” of geographic information, thus providing complementary and alternative geographic information from the products created by national mapping agencies.

scholarly journals Edge Computing: A Survey On the Hardware Requirements in the Internet of Things World

2019 ◽  
Vol 11 (4) ◽  
pp. 100 ◽  
Author(s):  
Maurizio Capra ◽  
Riccardo Peloso ◽  
Guido Masera ◽  
Massimo Ruo Roch ◽  
Maurizio Martina
Keyword(s):  
Internet Of Things ◽  
Mobile Devices ◽  
Information Exchange ◽  
Large Scale ◽  
Operating Time ◽  
Edge Computing ◽  
The Internet ◽  
Power Load ◽  
Battery Capacity ◽  
Iot Devices

In today’s world, ruled by a great amount of data and mobile devices, cloud-based systems are spreading all over. Such phenomenon increases the number of connected devices, broadcast bandwidth, and information exchange. These fine-grained interconnected systems, which enable the Internet connectivity for an extremely large number of facilities (far beyond the current number of devices) go by the name of Internet of Things (IoT). In this scenario, mobile devices have an operating time which is proportional to the battery capacity, the number of operations performed per cycle and the amount of exchanged data. Since the transmission of data to a central cloud represents a very energy-hungry operation, new computational paradigms have been implemented. The computation is not completely performed in the cloud, distributing the power load among the nodes of the system, and data are compressed to reduce the transmitted power requirements. In the edge-computing paradigm, part of the computational power is moved toward data collection sources, and, only after a first elaboration, collected data are sent to the central cloud server. Indeed, the “edge” term refers to the extremities of systems represented by IoT devices. This survey paper presents the hardware architectures of typical IoT devices and sums up many of the low power techniques which make them appealing for a large scale of applications. An overview of the newest research topics is discussed, besides a final example of a complete functioning system, embedding all the introduced features.

A Novel Approach to Location-Aware Scheduling of Workflows Over Edge Computing Resources

2020 ◽  
Vol 17 (3) ◽  
pp. 56-68
Author(s):  
Yin Li ◽  
Yuyin Ma ◽  
Ziyang Zeng
Keyword(s):  
Real World ◽  
Service Level Agreement ◽  
Service Level ◽  
Scientific Workflow ◽  
Edge Computing ◽  
Workflow Scheduling ◽  
Location Aware ◽  
Novel Approach ◽  
Negative Impacts ◽  
Multiple Metrics

Edge computing is pushing the frontier of computing applications, data, and services away from centralized nodes to the logical extremes of a network. A major technological challenge for workflow scheduling in the edge computing environment is cost reduction with service-level-agreement (SLA) constraints in terms of performance and quality-of-service requirements because real-world workflow applications are constantly subject to negative impacts (e.g., network congestions, unexpected long message delays, shrinking coverage, range of edge servers due to battery depletion. To address the above concern, we propose a novel approach to location-aware and proximity-constrained multi-workflow scheduling with edge computing resources). The proposed approach is capable of minimizing monetary costs with user-required workflow completion deadlines. It employs an evolutionary algorithm (i.e., the discrete firefly algorithm) for the generation of near-optimal scheduling decisions. For the validation purpose, the authors show that our proposed approach outperforms traditional peers in terms multiple metrics based on a real-world dataset of edge resource locations and multiple well-known scientific workflow templates.

scholarly journals Technology Enablers for Context-Aware Healthcare Applications

2011 ◽  
pp. 861-870
Author(s):  
Filipe Meneses ◽  
Adriano Moreira
Keyword(s):  
Wireless Networks ◽  
Mobile Phone ◽  
Mobile Devices ◽  
Added Value ◽  
Context Aware ◽  
Healthcare Applications ◽  
Technological Environment ◽  
Location Aware ◽  
Surrounding Environment

The increasing availability of mobile devices and wireless networks, and the tendency for them to become ubiquitous in our dally lives, creates a favourable technological environment for the emergence of new, simple, and added-value applications for healthcare. This chapter focuses on how context and location can be used in innovative applications and how to use a set of solutions and technologies that enable the development of innovative context and location-aware solutions for healthcare area. It shows how a mobile phone can be used to compute the level of familiarity of the user with the surrounding environment and how the familiarity level can be used in a number of situations.

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