Hossam Farag

Mr. Hossam Farag

orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 January 2018 in IEEE Sensors Journal
Verified
Journal Article
Closed access
HFHossam Farag
Hossam Farag
Mikael GidlundMikael Gidlund
Mikael Gidlund
POPatrik Osterberg
Patrik Osterberg
Industrial wireless sensor networks (IWSNs) designed for mission- and time-critical applications require timely and deterministic data delivery within stringent deadline bounds. Exceeding delay limits for such applications can lead to system malfunction or ultimately dangerous situations that can threaten human safety. In this paper, we propose Slot Stealing Medium Access Control (SS-MAC), an efficient SS-MAC protocol to guarantee predictable and timely channel access for time-critical data in IWSNs. In the proposed SS-MAC, aperiodic time-critical traffic opportunistically steals time slots assigned to periodic non-critical traffic. Additionally, a dynamic deadline-based scheduling is introduced to provide guaranteed channel access in emergency and event-based situations, where multiple sensor nodes are triggered simultaneously to transmit time-critical data to the controller. The proposed protocol is evaluated mathematically to provide the worst-case delay bound for the time-critical traffic. Performance comparisons are carried out between the proposed SS-MAC and WirelessHART standard and they show that, for the time-critical traffic, the proposed SS-MAC can achieve, at least, a reduction of almost 30% in the worst-case delay with a significant channel utilization efficiency.

19 December 2018 in IEEE Sensors Journal
Verified
Journal Article
Closed access
HFHossam Farag
Hossam Farag
Emiliano SisinniEmiliano Sisinni
Emiliano Sisinni
Mikael GidlundMikael Gidlund
Mikael Gidlund
PÖPatrik Österberg
Patrik Österberg

14 August 2020 in IEEE Internet of Things Journal
Verified
Journal Article
Closed access
HFHossam Farag
Hossam Farag
SGSimone Grimaldi
Simone Grimaldi
Mikael GidlundMikael Gidlund
Mikael Gidlund
PÖPatrik Österberg
Patrik Österberg
In the perspective of the emerging Industrial Internet of things (IIoT), the 6TiSCH working group has been created with the main goal to integrate the capabilities of the IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) with the IPv6 protocol stack. In order to support time-critical applications in IIoT, reliable real-time communication is a key requirement. Specifically, aperiodic critical traffic, such as emergency alarms, must be reliably delivered to the DODAG root within strict deadline bounds to avoid system failure or safety-critical situations. Currently, there is no mechanism defined in the 6TiSCH architecture for timely and reliably handling of such traffic and its prioritization over the non-critical one. In this paper, we introduce REA-6TiSCH, a reliable emergency-aware communication scheme to support real-time communications of emergency alarms in 6TiSCH networks. In REA-6TiSCH, the aperiodic emergency traffic is opportunistically enabled to hijack transmission cells pre-assigned for the regular periodic traffic in the TSCH schedule. Moreover, we introduce a distributed optimization scheme to improve the probability that an emergency flow is delivered successfully within its deadline bound. To the best of our knowledge, this is the first approach to incorporate emergency alarms in 6TiSCH networks. We evaluate the performance of REA-6TiSCH through extensive simulations and the results show the effectiveness of our proposed method in handling emergency traffic compared to Orchestra scheme. Additionally, we discuss the applicability of REA-6TiSCH and provide guidelines for real implementation in 6TiSCH networks.

1 December 2014
Verified
Conference Paper
Closed access
HFHossam Farag
Hossam Farag
MEM. Ehab
M. Ehab
Cognitive Radio (CR) is an intelligent technique for opportunistic access of idle resources. In CR, Spectrum sensing is one of its important key functionalities. It is used to sense the unused spectrum in an opportunistic manner. Energy detection constitutes a preferred approach for spectrum sensing in cognitive radio due to its simplicity and applicability. The conventional energy detection technique, which is based upon fixed threshold, is sensitive to noise uncertainty which is unavoidable in practical cases. This noise uncertainty gets the fixed threshold energy detector un-optimized in its performance. In this paper, an efficient energy detector is proposed for optimal CR performance. The proposed scheme is based upon a dynamic threshold energy detection algorithm, in which, the decision threshold is toggled between two levels based upon the average energy received from the primary user (PU) during a specified period of observation. Thresholds evaluations are based upon estimating the noise uncertainty factor. These thresholds are used to maximize the probability of detection (Pd) and minimize the probability of false alarm (Pfa). Theoretical analysis and simulation results show the effectiveness of the proposed scheme in comparison to the conventional energy detection method with less increase in complexity.

1 April 2014
Verified
Conference Paper
Closed access
HFHossam Farag
Hossam Farag
EMEhab Mahmoud Mohamed
Ehab Mahmoud Mohamed
Cognitive Radio (CR) is a regulated technique for opportunistic access of idle resources. In CR, Spectrum sensing is one of its important key functionalities. It is used to sense the unused spectrum in an opportunistic manner. Energy detection constitutes a preferred approach for spectrum sensing in cognitive radio due to its simplicity and applicability. The traditional energy detection technique, which is based upon fixed threshold, is sensitive to noise uncertainty which is unavoidable in practical cases. This noise uncertainty gets the fixed threshold energy detector un-optimized in its performance. In this paper, an efficient energy detector is proposed for optimal CR performance. The proposed scheme is a dynamic threshold energy detection algorithm, in which, two threshold levels are utilized based upon the average energy received from the primary user (PU) during a specified period of observation. Thresholds evaluations are based upon estimating the noise uncertainty factor. These thresholds are used to maximize the probability of detection (Pd) and minimize the probability of false alarm (Pfa). Theoretical analysis and simulation results show the effectiveness of the proposed scheme in comparison to the traditional energy detection method with less increase in complexity.

1 February 2017 in Pervasive and Mobile Computing
Verified
Journal Article
Closed access
HFHossam Farag
Hossam Farag
EMEhab Mahmoud Mohamed
Ehab Mahmoud Mohamed