Evidence map›Paper›PMID 38283301›Full record

ArticleIEEE internet of things journal2024

Orchestration and Management of Adaptive IoT-centric Distributed Applications.

Sehrish Amjad, Ahmed Akhtar, Muhammad Ali, Ayesha Afzal, Basit Shafiq, Jaideep Vaidya, Shafay Shamail, Omer Rana

Abstract read
In one paragraph

Article in IEEE internet of things journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sehrish AmjadDepartment of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan.
Ahmed AkhtarDepartment of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan.
Muhammad AliDepartment of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan.
Ayesha AfzalDepartment of Computer Science, Air University, Pakistan.
Basit ShafiqDepartment of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan.
Jaideep VaidyaRutgers University, Newark, NJ 07102.
Shafay ShamailDepartment of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan.
Omer RanaSchool of Computer Science & Informatics, Cardiff University, Cardiff, UK.

Funding

Supplement for high performance compute clustersR35GM134927 · NIGMS · RUTGERS THE STATE UNIV OF NJ NEWARK · PI VAIDYA, JAIDEEP · 2020 to 2024
$2.1M
NIGMS NIH HHS R35 GM134927
6 · The paper itself

Abstract

Current Internet of Things (IoT) devices provide a diverse range of functionalities, ranging from measurement and dissemination of sensory data observation, to computation services for real-time data stream processing. In extreme situations such as emergencies, a significant benefit of IoT devices is that they can help gain a more complete situational understanding of the environment. However, this requires the ability to utilize IoT resources while taking into account location, battery life, and other constraints of the underlying edge and IoT devices. A dynamic approach is proposed for orchestration and management of distributed workflow applications using services available in cloud data centers, deployed on servers, or IoT devices at the network edge. Our proposed approach is specifically designed for knowledge-driven business process workflows that are adaptive, interactive, evolvable and emergent. A comprehensive empirical evaluation shows that the proposed approach is effective and resilient to situational changes.

Indexed as

Edge ComputingIoT-centric workflowsKnowledge-driven business processesService orchestration

Identifiers

PMID38283301
PMCPMC10810342

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.