Admitting New Requests in Fog Networks According to Erlang B Distribution

Shafik, Wasswa; Matinkhah, S. Mojtaba

doi:10.1109/iraniancee.2019.8786518

Cited by 8 publications

(8 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, the model finalized the results diverge from that of Optimal merely by at most 3.91%. Lastly on the list are the variations in the graph domino influence from the quantity of UAVs in the scheme, the collective acknowledged data escalations with the number of UAVs depicting the average data received thus proper admission [30]. The Impact of blockages was further investigated per the cumulative received data.…”

Section: The Impact Of Blockagesmentioning

confidence: 99%

A 3-dimensional fast machine learning algorithm for mobile unmanned aerial vehicle base stations

Shafik

Matinkhah

Afolabi

et al. 2021

IJAAS

Self Cite

View full text Add to dashboard Cite

<p>The 5G technology is predicted to achieve the unoptimized millimeter Wave (mmWave) of 30-300 GHz bands. This unoptimized band because of the loss of mm-Wave bands, like path attenuation and propagation losses. Nonetheless, because of: (i) directional transmission paving way for beamforming to recompense for the path attenuation, and (ii) sophisticated placement concreteness of the base stations (BS) is the best alternative for array wireless communications in mmWave bands (that is to say 100-150 m). The advance in technology and innovation of unmanned aerial vehicles (UAVs) necessitates many opportunities and uncertainties. UAVs are agile and can fly all complexities if the terrains making ground robots unsuitable. The UAV may be managed either independently through aboard computers or distant controlled of a flight attendant on pulverized wireless communication links in our case 5G. Although a fast algorithm solved the problematic aspect of beam selection for 2-dimensional scenarios. This paper presents 3-dimensional scenarios for UAV. We modeled beam selection with environmental responsiveness in millimeter Wave UAV to accomplish close optimum assessments on the regular period through learning from the available situation.</p>

show abstract

Section: The Impact Of Blockagesmentioning

confidence: 99%

A 3-dimensional fast machine learning algorithm for mobile unmanned aerial vehicle base stations

Shafik

Matinkhah

Afolabi

et al. 2021

IJAAS

Self Cite

View full text Add to dashboard Cite

show abstract

“…Alternatively, considered the assumption that a WSN entailing of N nodes with sensing ability and one mobile sink, those sensor nodes collect files from the locality location and use multihops in forwarding to supply data to the closer mobile entities as shown in [20]. Also considered further assumed the transmission diameter a case in point a disk, of sensor nodes is positioned in this model demonstrated [21], this contributes to the efficiency of algorithm established on multiclassifiers [22], ensuring the two-stage fuzzy statistics envelopment exploration [23], and applicability and performance evaluation of models as detailed in [24].…”

Section:  mentioning

confidence: 99%

A Portable Fuzzy Sink Scheme for Wireless Sensor Network Life Expectancy Enhancement

Shafik¹,

Matinkhah²

2020

Preprint

View full text Add to dashboard Cite

Wireless Sensor Networks (WSNs) is considered to be a promising research area since it entails sensing capabilities. WSNs are confronted by fabricated explosion injection attacks and in return results into draining of vitality on sensor nodes routing mainly because of increased capabilities in a broad range of applications where sensor nodes use a battery as the power source. In this paper, we reveal and claim a state-of-the-art model to minimize vitality depletion of nodes within the network in return increases network period to more realistic stretch. It is revealed that the main cause is vitality consumption unbalances in different parts of the network direct resulting from having a static sink. More still, the network nodes neighboring the sink insistently partake in progressing data of other nodes to the sink. Consequently, the network nodes are supplementarily subjected to untimely vitality exhaustion. This paper mainly provides a novel movable (mobile) fuzzy logic sink approach and an intelligent system like expect systems that are able to scrutinize network situation, and make the superlative choice for spreading the network period robotically.

show abstract

“…In comparison to pre-4G technology, 5G will incorporate a variety of emerging wireless technologies, for example, Non-Orthogonal Multiple Access (NOMA), broad Multiple Input Multiple Output (MIMO), millimeter-wave (mm-Wave), and many more technologies for IoT networking [16][17][18][19][20][21]. Within Figure 1, an illustration of the high-level 5G system architecture is demonstrated.…”

Section: Introductionmentioning

confidence: 99%

“…5G is one of the widely popular areas of research for telecommunications professionals as the next wave of broadband networks. As a result, several reports on 5G networks have already been completed, [14][15][16][17][18]. O These articles discussed many potential research opportunities, like infrastructure, flexibility organization, traffic organization, privacy, security, and technological economic features, which are extremely important to consider during the 5G implementation.…”

Section: Introductionmentioning

confidence: 99%

Overview of 5G & Beyond Security

Shokoor

Shafik

Matinkhah

2022

EAI Endorsed Trans IoT

View full text Add to dashboard Cite

Network security is a crucial concern when it comes to computation, concerns like threats can have high consequences, and critical information will be shared with unauthorized persons. This paper presents a detailed survey on Fifth Generation (5G) and security aspect. This is more predictable since the core technology; the synonymous approach is possible with Fifth Generation (5G) and Beyond Technologies though with limited access. Many incidents have shown that the possibility of a hacked wireless network, not just impacts privacy and security worries, but also hinders the diverse dynamics of the ecosystem. Security attacks have grown in frequency and severity throughout the near past, making detection mechanisms harder.

show abstract

Admitting New Requests in Fog Networks According to Erlang B Distribution

Cited by 8 publications

References 12 publications

A 3-dimensional fast machine learning algorithm for mobile unmanned aerial vehicle base stations

A 3-dimensional fast machine learning algorithm for mobile unmanned aerial vehicle base stations

A Portable Fuzzy Sink Scheme for Wireless Sensor Network Life Expectancy Enhancement

Overview of 5G & Beyond Security

Contact Info

Product

Resources

About