The healthcare infrastructure requires robust security procedures, technologies, and policies due... more The healthcare infrastructure requires robust security procedures, technologies, and policies due to its critical
nature. Since the Internet of Things (IoT) with its diverse technologies has become an integral component of future healthcare
systems, its security requires a thorough analysis due to its
inherent security limitations that arise from resource constraints.
Existing communication technologies used for IoT connectivity,
such as 5G, provide communications security with the underlying
communication infrastructure to a certain level. However, the
evolving healthcare paradigm requires adaptive security procedures and technologies that can adapt to the varying resource
constraints of IoT devices. This need for adaptive security is
particularly pronounced when considering components outside
the ‘security sandbox of 5G’, such as IoT nodes and M2M
connections, which introduce additional security challenges. This
article brings forth the unique healthcare monitoring requirements and studies the existing encryption-based security approaches to provide the necessary security. Furthermore, this
research introduces a novel approach to optimizing security and
performance in IoT in healthcare, particularly in critical use cases
such as remote patient monitoring. Finally, the results from the
practical implementation demonstrate a marked improvement in
the system performance.
2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops): PhD Forum, Mar 11, 2024
Edge computing and Internet of Things (IoT) avail
a technological environment where everybody (h... more Edge computing and Internet of Things (IoT) avail
a technological environment where everybody (human, objects)
can join the internet to process, store, collect and exchange data
from the surrounding environment. Embedding of large scale
IoT applications to the network of distributed computational
resources has become a challenging part of the edge-cloud
continuum paradigm. Due to the high distance between the local
devices and the cloud, there would be an issue for latency sensitive
and energy-intensive applications like healthcare (i.e., patient
remote monitoring, wearable health devices), and AR/VR. The
edge computing paradigm resolves these challenges by providing
data resources and services closer to data sources and end devices
at the network’s edge. This research will focus on investigating
challenges and issues for the combined multi-tier orchestration
in edge-cloud continuum consisting of local edge nodes, edge
servers and cloud servers with emphasis on future 6G systems.
The PhD research will focus on resource and QoS-aware IoT
application deployment and resource orchestration in local edgecloud
continuum three-tier architecture in 6G.
2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), 2023
In the age of the Internet of Things (IoT) and
the expanding computing continuum, it’s crucial t... more In the age of the Internet of Things (IoT) and
the expanding computing continuum, it’s crucial to manage
and share resources at the edges of networks. This position
paper presents a new concept known as ’semantic slicing’. This
approach harnesses the power of artificial intelligence (AI),
wireless networks, edge computing, and sensing technologies
to enable novel applications, optimize resource allocation, and
streamline data processing and decision-making across complex
systems spanning the computing continuum. Semantic slicing
applies a deep understanding of the data and specific application
requirements to intelligently allocate resources and distribute
processing tasks in the computing continuum. This strategy
allows for the creation of systems that are not only more efficient
and responsive, but also better equipped to adapt to a variety of
applications and services.
Load balancing and workload distribution cause challenges for the management of IoT and distribut... more Load balancing and workload distribution cause challenges for the management of IoT and distributed systems in the edge computing environment. Swarm intelligence is a technology suitable for the management of distributed systems, networks, communication and routing protocols. Swarm intelligence-based PSO algorithms (particle swarm optimization) can be applied for load balancing and task scheduling in cloud computing environments operating through a broker agent. In distributed cloud environments, data is collected and then processed at the center of the cloud, rather than making decision at edge nodes closer to IoT infrastructures. Here, we develop an automated orchestration technique for clustered cloud architectures. An Autonomous Particle Swarm Optimization, called the A-PSO algorithm, is implemented that enables an edge node, such as a remote storage, to work as part of a decentralized, self-adaptive intelligent task scheduling and load balancing agant between resources in distr...
The healthcare infrastructure requires robust security procedures, technologies, and policies due... more The healthcare infrastructure requires robust security procedures, technologies, and policies due to its critical
nature. Since the Internet of Things (IoT) with its diverse technologies has become an integral component of future healthcare
systems, its security requires a thorough analysis due to its
inherent security limitations that arise from resource constraints.
Existing communication technologies used for IoT connectivity,
such as 5G, provide communications security with the underlying
communication infrastructure to a certain level. However, the
evolving healthcare paradigm requires adaptive security procedures and technologies that can adapt to the varying resource
constraints of IoT devices. This need for adaptive security is
particularly pronounced when considering components outside
the ‘security sandbox of 5G’, such as IoT nodes and M2M
connections, which introduce additional security challenges. This
article brings forth the unique healthcare monitoring requirements and studies the existing encryption-based security approaches to provide the necessary security. Furthermore, this
research introduces a novel approach to optimizing security and
performance in IoT in healthcare, particularly in critical use cases
such as remote patient monitoring. Finally, the results from the
practical implementation demonstrate a marked improvement in
the system performance.
2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops): PhD Forum, Mar 11, 2024
Edge computing and Internet of Things (IoT) avail
a technological environment where everybody (h... more Edge computing and Internet of Things (IoT) avail
a technological environment where everybody (human, objects)
can join the internet to process, store, collect and exchange data
from the surrounding environment. Embedding of large scale
IoT applications to the network of distributed computational
resources has become a challenging part of the edge-cloud
continuum paradigm. Due to the high distance between the local
devices and the cloud, there would be an issue for latency sensitive
and energy-intensive applications like healthcare (i.e., patient
remote monitoring, wearable health devices), and AR/VR. The
edge computing paradigm resolves these challenges by providing
data resources and services closer to data sources and end devices
at the network’s edge. This research will focus on investigating
challenges and issues for the combined multi-tier orchestration
in edge-cloud continuum consisting of local edge nodes, edge
servers and cloud servers with emphasis on future 6G systems.
The PhD research will focus on resource and QoS-aware IoT
application deployment and resource orchestration in local edgecloud
continuum three-tier architecture in 6G.
2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), 2023
In the age of the Internet of Things (IoT) and
the expanding computing continuum, it’s crucial t... more In the age of the Internet of Things (IoT) and
the expanding computing continuum, it’s crucial to manage
and share resources at the edges of networks. This position
paper presents a new concept known as ’semantic slicing’. This
approach harnesses the power of artificial intelligence (AI),
wireless networks, edge computing, and sensing technologies
to enable novel applications, optimize resource allocation, and
streamline data processing and decision-making across complex
systems spanning the computing continuum. Semantic slicing
applies a deep understanding of the data and specific application
requirements to intelligently allocate resources and distribute
processing tasks in the computing continuum. This strategy
allows for the creation of systems that are not only more efficient
and responsive, but also better equipped to adapt to a variety of
applications and services.
Load balancing and workload distribution cause challenges for the management of IoT and distribut... more Load balancing and workload distribution cause challenges for the management of IoT and distributed systems in the edge computing environment. Swarm intelligence is a technology suitable for the management of distributed systems, networks, communication and routing protocols. Swarm intelligence-based PSO algorithms (particle swarm optimization) can be applied for load balancing and task scheduling in cloud computing environments operating through a broker agent. In distributed cloud environments, data is collected and then processed at the center of the cloud, rather than making decision at edge nodes closer to IoT infrastructures. Here, we develop an automated orchestration technique for clustered cloud architectures. An Autonomous Particle Swarm Optimization, called the A-PSO algorithm, is implemented that enables an edge node, such as a remote storage, to work as part of a decentralized, self-adaptive intelligent task scheduling and load balancing agant between resources in distr...
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Papers by Hafiz Faheem Shahid
nature. Since the Internet of Things (IoT) with its diverse technologies has become an integral component of future healthcare
systems, its security requires a thorough analysis due to its
inherent security limitations that arise from resource constraints.
Existing communication technologies used for IoT connectivity,
such as 5G, provide communications security with the underlying
communication infrastructure to a certain level. However, the
evolving healthcare paradigm requires adaptive security procedures and technologies that can adapt to the varying resource
constraints of IoT devices. This need for adaptive security is
particularly pronounced when considering components outside
the ‘security sandbox of 5G’, such as IoT nodes and M2M
connections, which introduce additional security challenges. This
article brings forth the unique healthcare monitoring requirements and studies the existing encryption-based security approaches to provide the necessary security. Furthermore, this
research introduces a novel approach to optimizing security and
performance in IoT in healthcare, particularly in critical use cases
such as remote patient monitoring. Finally, the results from the
practical implementation demonstrate a marked improvement in
the system performance.
a technological environment where everybody (human, objects)
can join the internet to process, store, collect and exchange data
from the surrounding environment. Embedding of large scale
IoT applications to the network of distributed computational
resources has become a challenging part of the edge-cloud
continuum paradigm. Due to the high distance between the local
devices and the cloud, there would be an issue for latency sensitive
and energy-intensive applications like healthcare (i.e., patient
remote monitoring, wearable health devices), and AR/VR. The
edge computing paradigm resolves these challenges by providing
data resources and services closer to data sources and end devices
at the network’s edge. This research will focus on investigating
challenges and issues for the combined multi-tier orchestration
in edge-cloud continuum consisting of local edge nodes, edge
servers and cloud servers with emphasis on future 6G systems.
The PhD research will focus on resource and QoS-aware IoT
application deployment and resource orchestration in local edgecloud
continuum three-tier architecture in 6G.
the expanding computing continuum, it’s crucial to manage
and share resources at the edges of networks. This position
paper presents a new concept known as ’semantic slicing’. This
approach harnesses the power of artificial intelligence (AI),
wireless networks, edge computing, and sensing technologies
to enable novel applications, optimize resource allocation, and
streamline data processing and decision-making across complex
systems spanning the computing continuum. Semantic slicing
applies a deep understanding of the data and specific application
requirements to intelligently allocate resources and distribute
processing tasks in the computing continuum. This strategy
allows for the creation of systems that are not only more efficient
and responsive, but also better equipped to adapt to a variety of
applications and services.
nature. Since the Internet of Things (IoT) with its diverse technologies has become an integral component of future healthcare
systems, its security requires a thorough analysis due to its
inherent security limitations that arise from resource constraints.
Existing communication technologies used for IoT connectivity,
such as 5G, provide communications security with the underlying
communication infrastructure to a certain level. However, the
evolving healthcare paradigm requires adaptive security procedures and technologies that can adapt to the varying resource
constraints of IoT devices. This need for adaptive security is
particularly pronounced when considering components outside
the ‘security sandbox of 5G’, such as IoT nodes and M2M
connections, which introduce additional security challenges. This
article brings forth the unique healthcare monitoring requirements and studies the existing encryption-based security approaches to provide the necessary security. Furthermore, this
research introduces a novel approach to optimizing security and
performance in IoT in healthcare, particularly in critical use cases
such as remote patient monitoring. Finally, the results from the
practical implementation demonstrate a marked improvement in
the system performance.
a technological environment where everybody (human, objects)
can join the internet to process, store, collect and exchange data
from the surrounding environment. Embedding of large scale
IoT applications to the network of distributed computational
resources has become a challenging part of the edge-cloud
continuum paradigm. Due to the high distance between the local
devices and the cloud, there would be an issue for latency sensitive
and energy-intensive applications like healthcare (i.e., patient
remote monitoring, wearable health devices), and AR/VR. The
edge computing paradigm resolves these challenges by providing
data resources and services closer to data sources and end devices
at the network’s edge. This research will focus on investigating
challenges and issues for the combined multi-tier orchestration
in edge-cloud continuum consisting of local edge nodes, edge
servers and cloud servers with emphasis on future 6G systems.
The PhD research will focus on resource and QoS-aware IoT
application deployment and resource orchestration in local edgecloud
continuum three-tier architecture in 6G.
the expanding computing continuum, it’s crucial to manage
and share resources at the edges of networks. This position
paper presents a new concept known as ’semantic slicing’. This
approach harnesses the power of artificial intelligence (AI),
wireless networks, edge computing, and sensing technologies
to enable novel applications, optimize resource allocation, and
streamline data processing and decision-making across complex
systems spanning the computing continuum. Semantic slicing
applies a deep understanding of the data and specific application
requirements to intelligently allocate resources and distribute
processing tasks in the computing continuum. This strategy
allows for the creation of systems that are not only more efficient
and responsive, but also better equipped to adapt to a variety of
applications and services.