REAL-TIME SCHEDULING ALGORITHMS FOR WIRELESS SENSOR NETWORK

Circuits and Systems: An International Journal (CSIJ), Vol. 1, No. 1, January 2014
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REAL-TIME SCHEDULING ALGORITHMS FOR
WIRELESS SENSOR NETWORK
D.G.HARKUT1, M. S. ALI2 AND POONAM LOHIYA3
1H.O.D, PRMCEAM, BADNERA, 2PRINCIPAL, PRMCEAM, BADNERA AND 3M.E 2NDYR, PRMCEAM,
BADNERA
ABSTRACT
In Recent era, researchers attention is get magnetize towards a widely used technology known as a
wireless sensor networks (WSNs) used in the many of applications related to variety of fields including
military, healthcare monitoring, biological, home, vehicular monitoring, infrastructure monitoring,
building energy monitoring and industrial sensing. Many of applications in WSNs are real time
applications that are requested to run in real time way. To support such real time applications we need
Real Time Operating System (RTOS) which provides logically correct results and also deadline has to be
met. This paper presents an overview of existing scheduling algorithms which helps to schedule tasks in
real time systems. Next, we discuss work in sensornet operating system (OS) design. Then, the specialties
what sensornet OS should posses are discussed in detail. At last, we proposed Micro Controller OS-II
(µC/OS-II) with Earliest Deadline First (EDF) algorithm.
KEYWORDS
Wireless Sensor Network, Real Time Operating System, µC/OS-II operating system, Earliest Deadline
First.
1. INTRODUCTION
A WSN composed of number of wireless interconnected sensors. These are usually tiny
autonomous devices that are used to monitor some physical conditions or other values with their
sensors and use short range wireless link for communication between them and between higher
level systems. The measured values typically are temperature, humidity, light intensity; moisture
etc.WSN is found lot of interest due to great variety of applications like environmental
monitoring, military surveillance, biomedical systems, intelligent parking, healthcare applications
and industrial applications. Most of these applications related with the real world environments
and the delivery of data is limited to certain timing restraints [11]. It is a special type of real time
embedded systems where deadline is one of the critical parameter. Applications in embedded
systems are usually domain-specific. Most of the applications will require different operating
systems platform to provide various services. The basic functionalities of an OS include resource
abstraction, process management, memory management, interrupt management and device
management, scheduling policies, multithreading, and multitasking [1]. The OS also have a very
efficient inter-thread communication subsystem so that if a thread wants to communicate or
synchronize with each other, it should be able to do so without fail [18]. Over the past years we
have observed that OS plays an important role in building scalable distributed applications that
are efficient and dependable. WSNs typically does not use general purpose operating system
rather they use OS designed directly for them called special purpose OS i.e. RTOS. RTOS

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supports applications that meet deadlines and certain timing constraints to providing logically
correct results [17]. To meet the deadlines in Real time system we need to schedule the task
properly so that no one process goes under starvation or miss the deadline, for that different
scheduling techniques were used. The main objective of a real-time task scheduler is to meet the
deadline of tasks in the system. Mostly all the real-time systems in existence use multitasking and
pre-emption.
µC/OS-II is a real-time pre-emptive multitasking embedded OS kernel. A pre-emptive kernel is
used when system responsiveness is important; therefore, µC/OS-II and most commercials real-
time kernels are pre-emptive. µC/OS-II is a completely portable, ROMable, scalable, real-time
kernel. It provides services like task management, memory management and time management.
µC/OS-II kernel supports pre-emptive algorithms such as round-robin, rate monotonic scheduling
policy [29].
In this paper, we proposed µC/OS-II operating system for wireless networked sensors with
suitable scheduling policy. The remainder of this paper is organized as follows: Section 2
introduces related works of sensor network OS with suitable scheduling policy. Section 3
elaborates the task scheduling algorithms required to schedule the task in WSN. Section 4
discusses the specialties which a sensor OS should possess. Finally, section 5 concludes this
paper with some new ideas for future study.
2. RELATED WORK
The huge potential of WSN applications needs the RTOS to be suitable for different operating
environments, from a simple single-task event to a real-time multi-thread system. It means that
the RTOS must be resource-and context aware to minimize energy consumption. This section
presents a past work that has been done on embedded OS and also discussed scheduling policies.
In [14], Levis et al. proposed Berkeley’s TinyOS architecture which is designed for WSN.
TinyOS is a well-known operating system having light weight, low power and the Mote platform
has been widely used in many kinds of applications. It is currently a fundamental framework of
research on wireless sensor networks. The OS has a footprint that fits in 400 bytes and having
monolithic kernel. Since TinyOS kernel supports FIFO scheduling policy but FIFO scheduling
policy having some disadvantages that are also associated with the TinyOS scheduler. TinyOS
does not support real-time application; hence this OS is not a good choice to run real time
applications.
In [6], Dunkels et al. proposed ContikiOS as a lightweight and flexible OS for tiny network
sensors. It is having event-driven architecture written in C for WSN sensor nodes. It does not
employ any special kind of scheduling algorithm for real time applications. Events are classified
as synchronous and asynchronous and they are scheduled as they arrive. In case of interrupts,
interrupt handlers of an application runs with respect to their priority.
In [3], Bhatti et al. proposed the Mantis OS is energy efficient, multithreaded OS provides
scheduler which uses round robin scheduling policy within the each priority class. This policy
means the highest priority thread class can cause starve to lower priority thread. As compare to
TinyOS or Contiki scheduler, the Mantis OS scheduler is better because of pre-emptive priority
scheduling technique that may support real-time task. But still a better scheduling policy is
required to support real-time tasks.

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In [7], Eswaran et al. proposed Nano-RK a reservation-based energy-aware embedded OS having
small footprint with networking support. Nano-RK OS do not support end-to-end deadlines
guarantees associated with packet delivery. It provides only static scheduling. To support real-
time applications, Nano-RK uses rate monotonic scheduling algorithm which statically assigns
priorities to tasks.
In [4] [15], Cao Q et al. LiteOS, a multithreaded, Unix-like abstractions for sensor network.
This OS is more familiar to user. This OS schedule the real-time tasks with the help of
round robin algorithm. Because of some disadvantages of round robin algorithm we need
a better scheduling algorithm; therefore LiteOS is unable to support real-time applications.
Above discussion clarifies that some of the OSs provides the services for real-time application
with a priority based scheduling algorithms while others do not support for this.
3. REAL-TIME SCHEDULING ALGORITHM
Most of the tasks in WSN are requested to run in a real-time way. A system is said to be a real-
time system if it generates a result within a specified time so that job will complete its execution
before deadline and system will never fail if all jobs will complete its task before deadline. The
real time systems accepts commands from external peripherals, processes the data and then
perform desired action. Mostly we can divide real-time system into two main categories: Hard
real-time and soft real-time system. If a system is a hard real time then all task must be completed
before its deadline so that system will never face any catastrophic situation whereas in soft real
time system, if task miss their deadline then no such disastrous situation arise. As real-time
systems execute critical tasks, therefore it must be designed very carefully. For that, many
scheduling policy has been already designed [28].
A fundamental operation of an OS is scheduling the task. In order to meet a program’s temporal
requirements of real-time systems, it is of the utmost importance that the scheduling algorithm
should produce a predictable schedule, that is, at all times it should be known that which task is
going to be executed [9]. Figure 1 shows the basic scheduling algorithm function.
Make an
allocation
Schedule
processor
Is it feasible?
Display
Output
Declare
Failure

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Figure 1. Basic Function of Scheduling Algorithm
3.1 Different available scheduling algorithms and their characteristics
In Real-time systems scheduling algorithms are classified into two categories: Static algorithm
and Dynamic algorithm. Based on execution attributes of tasks, dynamic algorithm assigns
priorities at runtime. This algorithm allows switching of priorities between tasks. In contrast with
dynamic algorithm, a static algorithm assigns priorities at design time. All assigned priorities
remain fixed throughout the execution of task. Figure 2 gives the classification of available
scheduling algorithms for real-time systems [13] [16].
Figure 2. Types of Real time Scheduling Algorithms
Rate Monotonic (RM): In RM algorithm tasks have to be periodic in nature and deadline must
be equal to its period. Tasks are scheduled according to their period. The rate of task is the
inverse of its period. This algorithm implemented by assigning fixed priority to tasks, the higher
its rate, higher the priority.
Deadline Monotonic (DM): The other algorithm for scheduling all the real time tasks based on
their deadline is known as deadline monotonic. In this algorithm priority are decided by
considering relative deadline. If one task will get higher priority than the other then its relative
deadline must be shorter as compared to other tasks. RM and DM are identical except priorities
are automatically computed from rate of task or deadline.
Least Slack Time First (LST): It is type of dynamic algorithm which assigns priority
dynamically. Tasks are scheduled according to their slack: the smaller the slack, the higher the
priority. Slack is computed by using the difference between the deadline, the ready time and the
run time.
Earliest Deadline First (EDF): The most common dynamic priority scheduling algorithm for
real-time systems is the EDF. Here priorities are dynamically reassigned at run-time based on the
time still available for each task to reach its next deadline. Both static and dynamic systems are
scheduled by EDF algorithm.
Scheduling Algorithms
Static Priority-Driven
Fixed Priority Dynamic Priority
RM DM EDF LST

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Maintain a queue of tasks in ascending order of deadline so that whenever a processor gets free
then by using EDF scheduling policy task of the head of the queue will be assigned to the
processor. When new task arrives, its deadline will be compared with the deadline of currently
executing task, and in case if deadline of newly arrived task is closer to the current time, it will
receive the processor and the old task will be pre-empted and placed back in the queue. The EDF
algorithm is optimal compared with the other real-time algorithms and if task is not scheduled by
EDF then all other algorithms will fail to schedule that task [8] [19] [22]. As compared to other
algorithms EDF is simple to implement and gives much better utilization of processor.
In WSN, most of the tasks are appeared dynamically over the network. With the help of available
scheduling techniques like RM, DM, LST the most of the task are not scheduled before the
deadline and also this algorithms are responsible for data loss, overload and decline of
throughput. In most applications, the life of sensor nodes depends on their battery support. The
sensor node has limited battery energy and thus the sensor node must use available resources
effectively and manage the energy to extend the lifetime of the network as much as it can.
Therefore managing energy is very difficult problem while building a WSN.
This paper proposes an EDF scheduling algorithm which helps to schedule tasks dynamically
and enhance the throughput, reduce the overload and also helps to decrease energy consume in
data transmission and routing [22][27]. EDF improves the system’s performance and allows a
better exploitation of resources.
4. SENSOR OS DESIGN AND CHALLENGES
In this section we have discussed the challenges while designing a efficient, reliable OS for WSN.
4.1 Small Footprint. The current era of embedded processors demanding larger Read Only
Memory sizes with smaller Random Access Memory sizes [29]. Due to the limitation of memory
on a sensor node demands the OS to be designed with a very small footprint. It is a fundamental
characteristic of a sensor network OS and is the primary reason why so many sophisticated
embedded OS cannot be easily ported to sensor nodes [26].
4.2 Power management capability. Energy is important parameter in WSNs that must achieve
long lifetimes while operating on battery energy. Sensor nodes provide very limited battery life-
time. Thus possessing power management capability is essential, which helps to improve system
performance and extend the battery lifetime [5].
4.3 Portability. In WSN the hardware platforms are evolving day-by-day. Portability is
considered to be an important issue as everyone is working on their customized hardware
platforms. The OS should be designed in such a way that it is easily portable to different
hardware platforms with minimal changes.
4.4 Real-Time Guarantee. As most applications in WSN are time-sensitive in nature where data
must be forwarded and relayed on a timely basis, real-time guarantee is a necessary requirement
for such applications. By using real-time scheduler with proper scheduling technique real-time
constraints of the application can be satisfied [10].
4.5 Networking Stack. The networking stack facilitates developing distributed WSN
applications. The OS should support multi-hop wireless networking, routing. It also handles

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reliable packet transmission, multicasting, queue management, radio chip configuration, and
Medium Access Control (MAC) [26].
4.6 Programming Convenience. For application programmers OS should provide a convenient
programming environment. Many Sensor network applications are diverse and demanding. Hence
importance on development of sensor network applications programming convenience is of great
importance.
4.7 Dynamic Reprogramming. Dynamic reprogramming is an especially useful feature for
wireless networked sensors. It is the process of updating the software dynamically running on the
sensor nodes. Without reprogramming, it is difficult to perform operations like modification,
deletion or adding the contents in the software from the running system in WSN [23].
4.8 Customizability. Mostly all the software platforms developed for WSN is application
specific. Different applications demand different services from operating system [1]. These
requirements may be small footprint, real-time guarantees, reprogramming. The design of OS
should be in such a way that it should be easily customizable and extensible to various
applications.
4.9 Timeliness and Schedulability. Most sensor applications tend to be time-sensitive in nature
where processing must be completed within the defined time-bound otherwise system will fail.
Scheduling is technique for allocating tasks on processors to ensure that deadlines are to meet.
We need RTOS to support this scheduling technique.
Following table represents the summary of OS which supports the above mentioned challenges.
Table 1 Summary of OS
Features Tiny OS
Contiki
OS
Mantis OS
Nano-Rk
OS
Lite OS μC/OS-II
Priority based
scheduling No No No Yes Yes Yes
Real time
guarantee No No No Yes No Yes
Dynamic
Reprogramming
No Yes Yes Yes Yes Yes
Memory
Management
No No No No Yes Yes
Low Power
Mode
Yes Yes Yes Yes Yes Yes
Scheduling
algorithms used FIFO
Run time
scheduling
Round
Robin
Rate
Monotonic
Round
Robin
Rate
Monotonic
5. CONCLUSION AND FUTURE WORK
In this paper, we provide an overview of existing work; discuss the various scheduling algorithms
with their characteristics and also proposed EDF scheduling algorithm with their benefits over the
other real time scheduling algorithms. Next we discuss the challenges of in the OS design space.
In this paper, we discussed the µC/OS-II operating system with its features. µC/OS-II operating
system supports various real time applications in WSN. Currently, we are designing and

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implementing EDF algorithm for scheduling the entire tasks in WSN by using μC/OS-II RTOS.
Further study is required to improve performance.
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